All posts by USM

AI-Driven Personalized Product Recommendation: Use Cases and Benefits

In this competitive digital age, personalized product recommendations are necessary to enhance customer experience and propel sales. The more choices the customer has, the more the demand for products will increase.

Such is the power of AI-driven apps that recommend personalized products; these apps use machine learning for the analysis of a user’s buying behavior to recommend some personalized products. Herein, we have discussed a few top use cases and benefits of AI-powered product recommendations, along with the advantages of AI app development for industries.

What Are AI-Driven Recommendations?

It’s basically a recommendation app that is powered by AI and supports complex algorithms to scan through massive data sets in order to look for patterns in suggesting what to buy. Such a system can also include past purchases, browsing history, demographic information, and even social media activities. By knowing the preferences, AI apps are thus able to draw insights that help businesses in making a more engaging shopping experience and higher customer satisfaction and loyalty.

Moreover, AI-based recommendation apps involve machine learning techniques. As apps continue to train on new data, it tends to be more precise and relevant with time. Such ML algorithms can distinguish user interaction and know which products tend to convert more, hence adjust their recommendations based on the preferences of users.

How Do AI Recommendations Apps Work?

AI-powered product recommendation apps basically operate under two core functionalities: collaborative filtering and content-based filtering, as below. 

• Collaborative Filtering: This relies strictly on data about the ways users are interacting. Based on user interactions in purchasing products, the AI systems predict and recommend related products, which may increase conversions and sales.
• Content-Based Filtering: This works on the attributes of the product. If a customer always bought science fiction novels, it would suggest other books that fall in the same genre, are written by the same author, or carry similar keywords from the customer’s previous purchase.

Top Use Cases of AI-Driven Personalized Recommendation Apps!

Customizable AI-driven recommendation apps provide various advantages to businesses across various industries. Some are the following:

• E-commerce

The industry is witnessing a huge increase in conversion rates from personalized recommendations. E-commerce brands, such as Amazon, use modern AI-powered apps to provide personalized product recommendations according to that user’s history of both browsing and purchases.

• Streaming Services

Using AI-based recommendation applications, the leading streaming services, such as Netflix and Spotify, are better engaging their users. They suggest movies, shows, or songs based on a user’s taste, governed by the user’s viewing habits, user ratings, search behavior, and even the time of day when content is consumed.

• Travel and Hospitality

In the tourism industry, AI recommendation apps can be very helpful in personalizing recommendations to travelers. The companies can suggest appropriate destinations for users based on their travel behavior and preferences. Airbnb is contributing to more bookings as they use AI-powered recommendation applications.

• Fashion Retail

This would enable fashion retailers to use AI for personal styling advice. Analyzing a user’s previous purchases, preferences, and even social media activities, such retailers can suggest outfits or accessories matched to the unique style of the user, thus leading to higher customer satisfaction and sales.

• B2B Services

In the B2B sector, AI-driven recommendation can help identify potential suppliers or partners by following their history of procurement behaviors and understanding industry trends. This method will streamline the procurement processes and create value in business relationships.

Best Benefits of AI-Driven Recommendation Applications!

AI-driven product recommendation apps offer various benefits to businesses, such as the following:

• Enhanced Customer Experience

There are many reasons to believe that personalized recommendations will create a better shopping experience in terms of easing search, making it easier to identify and locate products based on customers’ preferences. Therefore, AI apps will save valuable customer time and make an experience smoother in the long run.

• Increased Sales and Conversion Rates

Studies suggest that individualized suggestions will have a positive impact on sales. Researchers have argued that 30% of e-commerce revenues depend on product recommendations. Showing customers products they are more likely to purchase might enhance the conversion rate, thereby allowing for easier revenue growth.

• Improved Customer Retention

A personalized experience drives customer loyalty. The moment the customer feels valued and understood is the moment they will be sure to return to the brand. AI-driven recommendation apps add to this as they will give customers suggestions that are relevant, thus growing the overall relationship between the customer and the brand.

• Better Inventory Management

Recommendations generated by AI software solutions can also be useful in inventory management. Based on the purchasing patterns and forecasting future requirements, businesses can maintain just the right stock levels without excess inventory. This means that waste is minimized and popular items are always in stock.  

• Insights into Customer Behaviours

Implementation of AI-driven recommendation systems gives a company insight about its customers’ behavior. A business can, by knowing trends and preferences via user interactions, guide its marketing strategies and the production of its products.

 

AI App Development for Personalized Recommendations

For the best possible benefits of AI-driven personalized recommendations, businesses need to pay attention to the following considerations in the AI app development process:

• Data Collection and Management.

A recommendation app works only based on the quality and quantity of data. A business must make sure to collect relevant information from the users by considering privacy laws. This collected data requires an appropriate management system for storage, processing, and analysis. 

• Choosing the Right Algorithms.

This is the point where the correct choice of algorithms makes the recommendation application work. Business has to first understand their needs and opt for either collaborative filtering, content-based filtering, or a hybrid that includes both.

• Continuous Learning and Adaptation.

Any successful AI-driven recommendation system must make continuous learning of user interactions. Over time, if a machine learning technique lets the system adapt, there will always be relevance in its recommendations and accuracy too. 

• User Interface Design.

The user interface is an important part of the effectiveness of personalized recommendations. A good UI should seamlessly integrate recommendations into the user experience without overwhelming the customer. Clear, intuitive layouts can enhance user engagement and satisfaction.

• Testing and Optimization.

Ongoing testing and optimization are necessary to refine the recommendation algorithms. Testing can provide insights into which recommendations drive engagement and conversions, allowing businesses to make data-driven adjustments.

 

Conclusion

AI-driven personalized product recommendation apps can significantly enhance customer experiences and drive business growth. By leveraging machine learning algorithms to analyze user behavior and preferences, companies can deliver tailored suggestions that meet the unique needs of each customer. Businesses can invest in AI app development for personalized recommendations to achieve benefits like increased sales and improved customer retention.

Partner with USM Business Systems and develop an advanced AI recommendation app that helps generate more value towards customer experiences and personalization.

 

[contact-form-7]

Generative AI in Healthcare: Use Cases and Future Outlook

Generative AI originates content or information through Artificial Intelligence (AI) technologies based on learning knowledge from prompts. In recent years, incredible applications of the generative AI have been found within several sectors, primarily in healthcare as well. This article discusses the integration benefits of generative AI in healthcare, use cases, challenges, return on investment, and the outlook for the future.

Use Cases of Generative AI in Healthcare

• Drug Discovery
  Generative AI basically comes up with novel molecular structures based on surveying huge chemical data after which it predicts those efficacy. This enhances the speed in drug discovery through rapid identification of promising compounds so that the expensive and time-consuming processes of making new drugs go down.
• Medical Imaging
  Generative AI generates highly detailed medical images and also supports the diagnosis of anomalies including tumors, fractures, or any other pathology. Through enhanced image quality and resolution, generative AI helps deliver accurate diagnoses most of the time by identifying some problems that could easily be left unnoticed by a human eye; early disease detection is also ensured. 
• Artificial Data Generation
  Generative AI can make synthetic medical datasets that reflect actual patient data while maintaining their privacy intact. These synthetic data become great means of model training, research, and development of AI-enabled solutions in ways that preserve patient confidentiality, thus allowing more representative and robust studies.
• Virtual Assistants
  AI-powered virtual assistants give personalized health-related advices, reminders for medication intake, and answers to other health-related questions. Such assistants increase patient participation, provide persistent support, and lighten the burden of healthcare professionals by automatically responding to routine inquiries and administrative questions.
• Administrative Automation
  Generative AI can automate administrative time-consuming tasks like scheduling appointments, managing patient records, and billing. This minimizes the burden of administrative tasks on healthcare providers, increases the efficiency of operations, and helps medical professionals to spend more time on patient care.

Challenges in the Acceptance of Generative AI Models

• Data privacy and security
  It is a significant challenge as protecting sensitive patient information will be critical because generative AI needs extensive data sets. Such an operation could create serious data breaches and misuse of private health information. 
• Regulatory Compliance
  Following healthcare regulations like HIPAA (Health Insurance Portability and Accountability Act) and other regional regulations is a complicated task since generative AI tools must be extensively tested and pass rigid regulatory compliance requirements before deployment. 
• Bias and Fairness
  Generative AI models can inherit the biases present in training data, making the predictions unfair or inaccurate. These models have to be free of bias and equitable across the patient population being diverse. 
• Integration with Existing Systems
  This results in integration into existing systems where legacy technologies abound, making generative AI tool integration into well-established workflows complicated and often frustrating for healthcare providers. 
• Data Quality and Availability
  AI models operate best on structured data of high quality, and many health organizations face the problem of patient data being either incomplete or not consistent, leading to AI generating less accurate insights. 
• Less availability of expertise
  Generative AI needs healthcare professionals and data scientists with the right skills. Shortage in AI and machine learning expertise in healthcare has limited its adoption. 
• Implementation Cost
  Establishing and integrating generative AI will be very costly since it demands advanced technologies, infrastructure, and highly skilled employees, making it unaffordable to a considerable number of small-sized healthcare institutions.

Future of Generative AI in Healthcare

Generative AI, when combined with precision medicine and personalized treatment planning, will open new vistas into more accurate diagnostics, the ultimate being diseases predicted even before symptomatology begins to occur. Even surgical systems shall become much more precise and low risk and ensure a rapid return to life before the patient gets operated on with AI-based systems.

Generative AI will also have a great role in increasing the accessibility of healthcare to all corners of the globe, especially in underprivileged areas. Affordable quality care will be provided through AI-based remote consultation and diagnosis in resource-poor regions. Further, AI will lead to the more independent health systems where routine work is performed by AI and experts can deal with critical cases, thereby increasing the efficiency of the whole system.

Conclusion

Generative AI is a revolutionary factor within the health world, ranging from discovering drugs all the way through making personalized treatment plans, to say the least of making radiological imagines. Another problem that existed was with regards to data privacy. Often overcoming barriers brings additional regulatory burden with it. Here, higher return on investment for better efficiency besides cost-cutting in patient care was noticed. This is much more achievable when full integration and maturity through health care have taken place. Indeed, the future of healthcare is tied up with this promise of generative AI, which promises solutions to global health problems.

Connect with Us today for Generative AI models!

[contact-form-7]

How Much Does it Cost to Develop A Chatbot App?

Chatbots are intelligent tools that interact and respond to customers’ queries like humans. These save a lot of time and money invested in providing 24*7 customer services.

Using Artificial Intelligence (AI), Natural Language Processing (NLP), and Machine Language (ML) languages, Chatbot apps instantly interpret user queries and respond in seconds. Further, the emotional intelligence of AI in bots detects the feelings behind the user messages and generates a matching response.

An online survey states that by the end of 2025, over 80% of businesses are expected to deploy chatbots apps. Hence, there is a high demand for chatbots, especially across eCommerce, healthcare, financial, insurance, travel, and telecom Industries.

Types of Chatbot Applications

It is important to differentiate the various types of chatbots available in the market to choose the appropriate one for your business. Here, we have listed three major types of chatbot apps that are best to integrate into existing mobile apps or web-based applications.

• AI-Based Chatbots

These are an advanced type of chatbots that uses the Artificial Intelligence and Machine Learning for self-learning. The bots upgrade the response system regularly depending upon the previous conversations. They ensure better customer satisfaction and provide a human-like conversational experience.

• Rule-Based Chatbots

The rule-based chatbots use if/then logic to provide helps to users in clarifying their queries. These bots detect certain keywords in the user questions and validate them with many other questions and pre-defined answers to give an accurate reply to users.

• Menu or Button-Based Chatbots

The structure of this type of chatbot is quite basic and widely used because of its simplicity. These bots offer several options in the form of a menu or buttons to the users and respond depending upon the user selection. However, these bots disappoint the users when the mentioned options do not match the query.

Best Features of Quick Responding Artificial Intelligence Chatbot Apps

The features included in the application rely on the needs of businesses. In this section, we have listed basic features that every business seeks to incorporate in their chatbots.

• Simple & Easy Interface

Keep an easy-to-use user interface or app design that can make your chatbots more engaging and appealing to the customers.

• Conversational Maturity with NLP

Chatbots understand the user queries or the conversation and provide accurate responses using the power of Natural Language Processing (NLP) technology.

• Chatbot with Emotional Quotient (EQ)

The emotional quotient (EQ) is an integral part of AI chatbots. It assists the bot in detecting emotions and tone in the customer query and responds appropriately like humans.  Hence, this feature provides a personalized user experience to customers.

• Geo Location

Tracking the location of customers will help the chatbots to give more relevant responses during the conversation. For instance, they can provide the contact number of the sales executive of a nearby branch to users.

• Free to Explore Solutions

Chatbots are capable of exploring vast data and find relative answers to customer problems. It can analyze the existing solutions from different sources for sending accurate responses.

• Payment system integration

This feature suits for e-commerce chatbots to create secured payment methods.

Are you looking out for a chatbot application for your business?

USM is the best mobile apps development company in the USA. We develop custom AI apps for enterprises. Our chatbot app development services fuel your business growth and reform the way you interact with your customers.  

Get a free quote for chatbot apps development project!

[contact-form-7]

Benefits of Interacting Chatbot apps for Your Business

• Better Customer Experience

The ultimate advantage of chatbots is that they respond 24*7 instantly and ensure improved customer experience.

• Sales Automation

Apart from answering questions, bots automate the end-to-end sales process. Chatbots are the approach for brands to strengthen relationships with customers.  By analyzing consumer purchasing patterns and search patterns, marketplace chatbots generate leads for businesses. In this way, they help businesses to engage customers and make more sales.

• Insight Into Customer Behaviour

Businesses can get valuable insights into customer behavior from chatbot conversations. Based on the customer queries, businesses can identify which products have more demand in the market. It helps to make market strategies for promoting goods and also optimize the chatbot content to provide the best answers.

Use Cases of AI  Chatbots in Business

• Booking Bots

You can book or schedule the appointment automatically with AI bots. When users book an appointment, it creates an event and sends reminders to both the customer and business representative. These bots are also available in the travel, recruiting, and entertainment industries.

• Customer Support Chatbots

Customer support is the basic service of chatbots, and you can find these types of chatbots on every website. The features like availability, live chat, and quick response make them an ideal tool for customer service.

• Chatbot Use Cases in Marketing

To generate leads, collect customer emails, simplify product prices to customers, most businesses are deploying chatbots across their marketing channels.

• Entertainment Chatbots

These intelligent chatbots improve audience engagement by giving personalized recommendations of events, shows, and movies.

Are you looking for chatbot apps developers?

USM has over two decades of industry experience in custom chatbot apps development. Get in Touch!

[contact-form-7]

Cost to Develop an AI Chatbot Application

Now you know about all the benefits and use cases of chatbots, it’s time to check the cost to build a chatbot application for your business. The approximate cost to develop your bot with minimum functionalities cost around $30,000 to $80,000.

This estimated cost might vary based on the app’s platform (Android, iOS, Windows), App User Interface, app features, development team size, and location of mobile app developers you choose.

Conclusion

Chatbots are exciting and innovative tools to upgrade the customer experience. These give instant responses to the users and engage them like humans.

Build your Business Chatbot with Top Chatbot Development Company

Being the best mobile apps development company, USM develops full-fledged chatbot apps within your budget.

[contact-form-7]

Artificial Intelligence (AI) in Food Industry

Among all other sectors, the food and beverages processing industry still has not adopted revolutionizing digital technologies like AI, Machine Learning (ML), and Internet-of-Technology (IoT). The sector is progressing slowly and generating fewer contributions to the domestic and national economy.

But, since the past few years, food and beverage processing companies are highly switching to integrate AI capabilities in their systems or applications to enhance work efficiency. According to research reports, it is expected that the food processing industry will create over $150 billion business by the end of 2022 through leveraging AI capabilities.

AI technology will play a crucial role in the future of businesses across all sectors (The Significance Of AI Technology By Industry) and the food processing and handling industry is one of them. The use of Artificial Intelligence in Food Processing has been witnessing rapid growth in recent years.

Food and beverages processing companies are increasingly embracing AI technologies for improving operational efficiencies and delivering consumer products on time to catch up with the market demand opportunities. They are enjoying the benefits of AI in the Food Industry. In this article, we guide you few significant AI use cases in the food and beverages industry.

Recommend To Read: Artificial Intelligence In Agriculture & Food Process

AI Use Cases In Food and Beverages Industry

In this 21st century, modernizing food processing with AI technology is essential to balance the supply and demand, strengthen the distribution network, and build brand reliability on delivering products on time. Because a food processing company has to use AI-like technologies to fasten the production and monitor the entire inventory and warehouse operation virtually to never give a chance for a single disruption across their operations.

This is why AI in food and beverage industry has become a hot topic. Its automation and intelligence capabilities are flagging a green signal for the increasing use of artificial intelligence in the food processing industry.

Let us discuss a few popular applications of AI in food and beverage industry that assist companies in dealing with challenges related to supply, distribution and logistics, employee productivity, and warehouse management like operations.

Get in Touch

[contact-form-7]

Key Applications Of Artificial Intelligence (AI) In Food Industry

1. AI In Food Industry For Sorting Raw Products

It is the best application of Artificial Intelligence in the Food Industry. Proper sorting of food products is one of the greatest challenges for the consumer products manufacturing facilities because the feedstock we receive from various farmers is not identical or uniform.

Once you have a look at the different fruits & vegetables like carrot, apple, grapes, tomato, orange, and many more will have their shapes and sizes. Food processing plants are required to segregate millions of raw products depending on color, shape, and size. Manual grading, sorting, and peeling-like functions will consume hours of the time of labor. But, the use of Artificial Intelligence in food processing operations will automate all these functions and improve work efficiency. The automation systems use various tools and technologies and offer these benefits:

• Enhancement of speed in sorting.
• Yield improvement
• Minimization of labor costs.
• Reduces wastage and improves production

Hence, food growers, packers, and processors are all using AI and IoT sensor-based advanced equipment and machinery to sort or peel several fresh food products to exploit output and reduce wastage.

For instance, TOMRA is a top sensor-based food processing machine manufacturing company in the world. It offers a range of advanced processing machinery that use AI and are embedded with IoT sensors to improve productivity and save time in sorting, peeling, and other initial operations.

Besides, a Japanese food company is also using TensorFlow machine learning technology to detect the oddities instantly in their diced potatoes. The company found that these AI systems are working more accurately beyond expectations. It became a significant advantage in their production. The company is further planning to expand AI utilization to reap all the benefits of AI in the Food Industry.

Have any AI & ML Project idea visit: Artificial intelligence in Manufacturing

2. AI in Food Industry For Ensuring Personal Hygiene

It is one of the best examples of Artificial Intelligence in the Food Industry. Since we are living in a COVID environment, all employees (who are involved in food processing) need to wear the mask, head caps, and hand gloves to ensure food safety.

As we care about our kitchen, food processing companies will also have to maintain hygiene to ensure the quality of the end products. On the other side, personal and plant hygiene is necessary to make sure that the plant is compliant with the rules and regulations of higher authorities.

The software development companies are making use of AI and ML to develop Facial recognition apps and solutions that monitor employees 24*7 to check whether they are following all hygiene protocols or not.

Hence, AI-powered facial and object recognition software solutions ensure 99.9% of accuracy in monitoring workers in real-time and taking screens of people who violate the safety precautions across the production line.

Recommend to Read: Best Facial Recognition Apps currently available on iOS and Android

3. AI in Food Industry For Decision Making

The role of artificial intelligence in food industry has a high demand for instant decision making and optimizing business results.

AI is not only helping food processing companies in making sorting processes easier and creating the best flavor combinations. The role of AI in food industry is also engaged in assisting food companies in deriving valuable insights into sales and business growth tactics.

For instance, knowing customer taste preferences and producing products that ensure new tastes and match the preferences of consumers are two big deals for food products manufacturing companies.

Here, AI comes into the picture. AI software, coupled with ML and deep learning algorithms, involves extracting useful business insights from vast data input. Based on the data related to the previous product’s demand and ingredients added in it to enrich its flavor, AI applications will create extremely new combinations that enhance the product’s tastes.

Hence, AI in food and beverage industry would help companies take immediate decisions and improve production operations.

4. AI For Faster Equipment Cleaning Process

It is one of the best AI use cases in food and beverages sector. In food processing industries, maintaining proper cleanliness is the most difficult task to handle or deal with.

Most of the food processing companies say they are very much clean like white paper because most of the process involves the automation process. No human labor is involved in the processing.

The method or procedure currently we are following has no sensors by which it cannot see what is happening inside the equipment. Due to this reason, companies are designing the procedure in such a way that it should run as long as required.

Companies are modernizing food processing with AI in many ways. AI-based self-optimizing clean-in-place tools are one of them. For the testing process, it uses optical fluorescence & ultrasonic sensing imaging technologies to know how much microbial debris & food is left in the equipment or inside the device.

Recommend To Read: Top 10 Use Cases Of Artificial Intelligence In The Manufacturing Industry

5. Developing new products

It is a popular application of Artificial Intelligence in food industry. AI in food and beverage industry is gaining popularity for its intelligence in offering the best flavor combinations to increase sales and generate profits for companies.

Since food service industry deals will produce products in various spices, ingredients, and flavors, it is challenging for companies to manufacture products that what customers are exactly looking out for. But, advanced technologies like AI can tackle this with ease. With the help of AI in the production process, food service companies can derive the probability of customer preferences and create taste-rich products for consumers.

Yes. Most of the food processing and packaging industries use AI and produce the best products in the market.

For instance, in the USA, the world’s biggest beverages manufacturer and supplier Coca-Cola has installed self-service soft drink fountains and allowed customers to personalize their drink choice. As per their taste preferences, customers can create thousands of drinks by selecting different flavors to their base flavors.

These fountains are programmed with AI software that can process vast data sets related to consumer taste preferences. Thanks to such advanced AI technology-enabled machines. The core advantage of this AI system is it recommends new flavor combinations and lets customers enjoy a new taste.

6. Streamlining The Supply Chain

It is the best examples of Artificial Intelligence in the food industry. While automating the entire food processing functions, AI technology is widely used for making the supply chain operations compliant with the rules and regulations of the specific authorities.

This AI application for the food processing industry can modernize the supply chain operations and maintain transparency from load pickup and warehouse shifting to distribution.

Here are a few benefits of AI in supply chain management:

• AI ensures high safety across the supply chain
• AI offers a transparent supply chain management system
• Better Inventory management
• Efficient maintenance of warehouse
• Low operational costs
• 100% delivery is as scheduled
• 24/7 product monitoring
• Reduces operational downtime
• Overall, AI augments end-to-end functions

Now, we will have a brief discussion on what challenges are hampering the use and growth of AI in food and beverage industry.

Challenges Of AI In The Food Industry

Though the impact of artificial intelligence in food industry is positive way, the technology is still facing a few challenges to roll out across the global food processing and handling sector. Here are a few challenges of AI in the food industry.

• Lack of proper awareness of implementing the features of AI
• Lack of knowledge on how AI technology improves processes and assists companies in achieving business objectives.
• In the initial phase, companies are facing failures in training the AI machines, systems, and applications with the right set of data.
• Lack of proper training to employees to work along with intelligent and advanced AI applications
• Since the cost of AI implementation and integration is quite expensive, the food processing service companies are going back to adopting AI technologies for automating their processes.

These are a few core challenges of AI in the food industry. To bring a revolution in the growth of AI, the companies need to get advice from the AI development companies. Being the best AI services and solutions provider (USA, India, & UAE), USM Business systems builds an efficient and powerful automation solution for optimizing your food business.

Get a free app quote!

Final Words

The benefits of AI in the Food Industry are incredible. AI will modernize the food processing industry and take it to new heights. The food industry is at its initial phase to completely adopt AI technology.

The top mobile app development service providers would help you create results-driven AI consultancy and app development services and solutions.

Are you looking to integrate AI solutions to automate your food processing and packages business?

Let’s connect with our AI experts & discuss your app idea.

[contact-form-7]

 

How to Develop an AI-Powered Recruitment Platform?

Over the past few years, there has been a rapid transformation in the recruitment landscape due to growing expectations for accuracy and diversity in hiring processes. Traditional recruiting methods are sluggish to handle the intricate hiring needs of modern businesses. Thus, companies are using artificial intelligence technology-powered tools to streamline the employment process and bring innovation to the process.

Artificial Intelligence (AI) can help organizations hire the right candidates more quickly and precisely by automating the process from resume screening to profile matching. But creating an AI-driven hiring platform is not that easy. It needs a deep understanding of both conventional recruiting models and AI potentialities in the recruiting landscape.

This article will guide you through the fundamental processes of developing an AI-powered hiring platform. We will also share insights and strategies for success in handling recruiting challenges with AI applications.

Core Features of an AI-Powered Recruitment Platform

Developing an AI-powered recruitment platform requires understanding key features that would make it truly effective and exceptional. Such features should be designed in a manner to automate, smoothen, and upgrade various recruitment processes at work, through which one can assure better hiring decisions that result in enhanced workforce efficiency.

• Automated Resume Screening:

One of the trickiest and most time-consuming processes of hiring is reviewing hundreds of resumes to shortlist a quality one. By independently scanning and sorting resumes based on predefined criteria like education, talents, and experience, AI can significantly reduce the workload.

Only the top candidates advance to the next round of the hiring process because these algorithms may be trained to recognize patterns in successful candidates and apply them to the evaluation of new candidates.

• Profile Matching and Shortlisting:

Another important factor of AI-powered recruitment platforms is their ability to match candidate profiles with job descriptions. Candidate profiles and job descriptions can be assessed using machine learning techniques in AI to find the right fit.

These algorithms make use of background cultural fit, growth potential, and even predictive performance data, not just simple keyword matching. This enables the individuals recommended to the customer by this platform not only to be qualified for the job but also to have every possibility of succeeding in their position.

• Virtual Assistant and Chatbot Support:

AI-driven chatbots can improve the applicant experience by interacting with applicants around the clock, responding to their inquiries, keeping them informed about the progress of their applicants, and even doing the initial screening interviews. So, the chatbot improves overall engagement and communication between the recruiter and the candidate.

• Predictive Analysis:

Predictive analysis helps with data-driven decision-making capabilities. Artificial intelligence can evaluate candidate profiles, hiring history, and other relevant data to determine a candidate’s likelihood of success in a given role. Predictive analysis helps recruiters make better decisions that increase the success rate and return on investment.

• Bias Mitigation:

AI-driven platforms mitigate the risk of unconscious bias when bringing objectivity into the evaluation process. Moreover, AI algorithms can be constantly checked and readjusted to make sure that they remain bias-free, thereby achieving further fairness in the recruitment process.

Step-by-Step Procedure to Develop an AI-Powered Recruitment Platform

Step 1: Research and Analysis of the Market

Detailed market research is required before the development phase. This includes understanding the current recruitment technology, finding any gaps in the current solutions, and assessing the demands of your target market. Talk to potential users, HR specialists, and recruiters to learn more about the functionalities and features they need.

Step 2: Define the Core Features

The next step is to establish the essential features and functionalities of your platform, depending on your market research. They include the core AI-driven features previously covered, such as chatbots, candidate-matching algorithms, automated resume screening, predictive analytics, etc. Include unique features that would give your recruitment platform a competitive edge. Also, map out a well-defined user experience journey for both recruiters and candidates to make the platform user-friendly.

Step 3: Selecting the Right AI Technology

Selecting the right technology is an essential part of the mobile app development process. Depending on your requirements, you can choose AI and machine learning tools and frameworks, including NLP libraries and data analytic tools. Besides, consider the demands of data storage and processing to make sure that the chosen technology stack will be able to safely and effectively process large volumes of data. This analysis makes your Android app development and iOS app development successful.

Step 4: Design and Development

Recruiting app design is a stage at which you do detailed wireframing and prototype the UI to ensure it provides an effortless experience from both the recruiter and candidate sides. At this phase of mobile application development, your team will start coding the front-end and back-end features using agile methods of development. An expert mobile app development team with AI developers and UX/UI designers can help ensure all areas of the AI recruiting platform for Android and iOS are fully covered.

Step 5: Unified Integrations

The integration of external supporting tools and applications into the AI hiring platform is complex and requires some proper strategizing on your part. First of all, use relevant datasets that may be resumes, job descriptions, or historical data on hiring to train AI and machine learning models. After training, these models need to be integrated with the core functionalities of the platform, such as resume screening and candidate matching.

Step 6: Thorough Testing

As a part of the development process, testing makes sure your platform is dependable and highly functional. The performance, security requirements, accuracy, and dependability of AI algorithms should all be tested to ensure the quality of your AI-powered recruiting application.

Step 7: Mobile App Deployment

Deploy with a minimal amount of downtime since this will be critical to a smooth transition for users. This phase may yield valuable benefits if rolled out by first presenting your beta version to a small number of users for feedback prior to release. This allows you to make any necessary adjustments based on real-world usage.

Step 8: Post-Launch Support

Monitor how your AI recruiting platform works, such as user interactions, the accuracy of AI functionalities, and satisfaction scores. Use this data to make continuous improvements by refining AI algorithms, adding new features, or improving UI. Not only will it keep your platform competitive, but with regular updates and improvements, it’s going to ensure that it remains competitive for the evolving demands of both recruiters and candidates.

How Much Does It Cost to Develop an AI-Powered Recruitment Platform?

The cost associated with developing an AI-powered recruitment platform varies depending on many factors. Hiring an expert AI development team and investing in an advanced technology stack are the major costs. Further, costs are impacted by data processing, acquisition, and storage, especially when huge datasets are needed to train AI models.

The average cost of AI recruiting platform development falls between $80,000 and $100,000, while a more sophisticated platform might cost between $150,000 and $250,000. Although there are significant upfront expenses associated with AI development, the long-term advantages of increased hiring effectiveness and better candidate matching can justify your AI investments.

Conclusion

Creating an AI-powered recruitment platform is a challenging but worthwhile project that can greatly improve the efficiency of hiring procedures. AI platforms have the potential to revolutionize recruitment processes by automating candidate matching, resume screening, and predictive analysis-like tasks.

However, careful planning is required for the development process, from conducting market research to choosing the best AI technology. Even if the initial costs seem to be high, the long-term advantages make AI development worth it.

If you are looking to integrate AI into your recruitment process or develop an AI-powered hiring application from scratch, USM Business Systems is the right AI development company to meet your AI software development needs.

Get in touch with USM Business Systems.

[contact-form-7]

Complete Guide to Location Based App Development

How Much Does It Cost to Develop Location-based or Location Tracking Mobile Apps?

How Much Does It Cost to Develop a Location Tracking Mobile Apps?

In the wake of emerging privacy dreads worldwide, the integration of location-based services in mobile apps is necessary. Businesses around the globe are already on their way to add location-based functionalities into their existing mobile apps for providing more security and qualitative digital services to their audience.

Dedicated location tracking mobile apps allow users to locate their places, find unfamiliar destination areas, track vehicles, and many more. These are the best advantages of mobile apps that are featured with location-based services.

The best example of a location-based app is Uber, an online cab booking application for android and iOS. These applications allow users to share their location to family or other for security purpose. Geolocation-based mobile apps development help businesses ensure the security of users in needed times. Besides, food delivery, medicine delivery mobile apps are also enabled with location-tracking features.

To help enterprises better understand the advantages and opportunities of GPS apps development, we have articulated a list of the best location-based apps and their use cases across industries.

Definition of Geolocation Tracking Mobile Apps

The term Geolocation tracking refers to tracing geographical information of users’ devices. Be it an android device, iOS smartphone, or any other trackers with GPS chip, GPS devices or applications tracks are helpful as location navigators and tracks precise geographic data.

Must-have Features Of Location-based Mobile Apps

The features and functionalities of the app will decide the success of a mobile application. If you would like to invest in location-based mobile apps development, you should not ignore the below three significant features.

• Eye appealing User Interface or User Experience design
• Integration of in-app Google Maps
• Flexibility to find and share current location
• Display distance and time between the source and destination places
• Location-based mobile app should show the shortest route to users
• Pointing precise location of the users’ device
• Voice guidance to reach the destination
• Location-based push notifications, etc.

These are must-have features of location-based apps.

Benefits Of Location-based Apps Development For Businesses

95% of global organizations are implementing location-based services in apps to reach more targeted customers. In particular, 90% of enterprises across the USA have enabled location-tracking services in their mobile apps.

The companies are focusing on integrating GPS services in Weather reporting apps, Social media apps, Travel booking apps, Photo or video editing or streaming apps, and many more. These are a few leading app categories for which businesses have enabled location-based services in the country.

We have picked up a few advantages of location-based apps development for businesses. If you are in dilemma to analyze the significance of GPS applications development, here are the reasons why companies around the world are integrating GPS functionality in trending mobile apps like Uber.

• Location aware apps in the transport industry allows businesses to deliver better customer-centric and geographic area-specific services
• Location-tracking applications help online travel booking service providers to precisely spot the user’s location and reach them without hassle.
• GPS tracking systems also help e-Commerce players track location and customers’ preferences and deliver more personalized services to them.
• Geolocation-based AR applications help real-estate companies offer virtual tour services to their patrons.
• Location-based marketing strategies help marketers reach out to geographically targeted audiences faster than ever.
• Strategic use of location-based marketing services in mobile apps makes businesses legends in their native places.
• Dedicated GPS trackers help users locate their vehicles, smart accessories, and even kids. It will increase customer loyalty towards the brand.
• Geolocation tracking healthcare apps help users find the nearest locations of healthcare service providers and get diagnosed in an emergency.
• Implementation of location tracking functionality in fitness apps allows users to position the current location of the users and distance walked in a day.

 

Which Industries Are Beneficial With Location-based Apps Development?

Location-based mobile apps are gaining increasing popularity in the market. Every industry is looking ahead to develop location-based apps to provide better services to their audience. Let us take a look at how industries are implementing location-based service apps.

Location-based Apps Use Cases by Industry

1. Use cases of location-aware apps in the Retail Industry

Walmart and IKEA like the biggest retailers are offering geolocation tracking apps to provide the best in-store experience to their customers. These location-based service applications use GPS signals to allow customers to find the nearest retail store to their geographic area and get the essentials faster.

IKEA-like leading retailers are also implementing beacon indoor navigation systems to assist targeted customers in reaching desired locations with ease.

Food delivery apps like Grubhub and Uber Eats also comes under the retail sector. These apps are implemented using a geolocation tracking feature. This feature allows users to track their orders in real-time on maps.

2. Applications of location tracking apps in Transportation

The best use case of location-based apps in the travel industry is tracking vehicles through GPS signals.

Uber-like popular GPS-enabled mobile time tracking app or online cab booking app for android/iOS use tracks user’s location to pair them with nearest drivers for quick pick up. This location tracking feature of Uber helps ueesers to track their cab and the estimated time of its arrival in real-time.

GetTaxi, the best online taxi booking app in the UK, is also featured with GPS tracking capabilities to monitor their rides continuously.

3. Geolocation apps use cases in Banking and Finance.

Location-based apps development offers plenty of benefits to both bankers and their customers. Banking mobile apps for android and iOS with geolocation feature advanced mobile banking apps security level.

The GPS tracking mobile banking apps determines whether the transaction aligns within the user’s mobile usual location or not. These insights would help bankers verify the clients’ identity based on GPS information, prevent fraudulent transactions, and send alerts to the account holders.

4. Ecommerce Location-based apps use cases

The demand for location-aware mobile apps development from e-Commerce industry players is increasing at a rapid pace. To provide a more personalized online shopping experience, e-commerce giants are enabling their marketplace apps geolocation tracking capabilities.

Besides, by tracking user’s location and their purchasing behavior, intelligent mobile apps allow businesses to run a personalized sales approach by sending location-based product offers and messages to the user’s smartphone.

5. Uses of location tracking mobile apps in Automotive

Here is another industry which is adopted GPS tracking apps to a greater extent. Using the Internet-of-Things technology-enabled sensors, the location-based mobile apps playing a key role in monitoring and managing the fleet all the time.

Onfleet, GeoTab, and US Fleet Tracking are a few famous vehicle tracking and asset management apps in the USA. These apps with built-in geolocation features track vehicles or fleets in real-time continuously and give information about the live location of vehicles or assets.

Would you invest in creating GeoTab like the best Fleet tracking apps?

Get in Touch!

[contact-form-7]

6. Advantages of location-based mobile apps in Media and Entertainment

Most used and popular social media apps or chatting apps like Instagram and WhatsApp are enabling location tracking and sharing functionalities. These apps allow users to view the map, search for locations, and send their current locations to contacts.

Grindr-like location-based social networking and online dating applications are enabling geolocation capacities to help users find the proximity of their connections. The GPS-based dating apps also give the flexibility to turn off the location-aware feature if they want.

Which Technologies Are Used in Location-based Apps Development?

Technologies might vary based on the application type. I mean to convey that technologies used for outdoor navigation apps development like Google Maps will be different from the technologies used for indoor navigation or in-app location-enabled apps development.

Required technologies for outdoor location-tracking apps

• GPS technology to receive signals from satellites and locate the destinations
• Assisted GPS technology for optimizing the accuracy of the GPS location
• Wi-Fi technology to collect data from the internet and position places with great accuracy.
• Cell ID to determine the location of a device when GPS signals are poor and inaccurate to locate spaces.
• The IoT technology to collect data for sensors equipped on devices and track location coordinates with 100% accuracy.

Required technologies for Indoor location-tracking apps

Indoor location tracking apps are best in navigating the users inside shopping malls, commercial buildings, etc. These types of location-tracking applications direct the users to the destination area inside a building from the place where they stand.

Here are the most used and required technologies for indoor location-tracking apps development.

• Geofencing Technology, in combination with GPS, cellular, and Wi-Fi technologies, locates the users when they enter into virtual boundaries and guides them towards the destination.
• iBeacon positioning technology using Bluetooth Low Energy signals to broadcast signals and allow users to reach locations when the users reach in-built beacons inside the building.

Are you interested in the development of Uber-like location-aware service apps?

[contact-form-7]

 

Which Tools Are Used To Create Location-based Apps?

The above technologies will play a vital role in location-based application development to enable geolocation functionality. To create the best location tracking mobile apps, one must integrate the app with third-party tools, including,

Most of the location-tracking service apps use Google Maps to provide accurate navigation through the shortest routes to the users.  Here are the few Google APIs used for location-based apps for android app /iOS app development.

Tools for GPS Navigation App development for Android OS

• Google Maps API
• Google Places API
• Google Geolocation API
• Google Maps Directions API
• Google Distance Matrix API
• Google Maps Android SDK
• MapView class
• Open Street Map

Tools used for GPS tracking application development for iPhone OS

• Google Maps SDK for iOS
• Apple Maps Kit
• Core Location API
• Google Maps API

 Technology stack and tools are also key factors that decide the cost of GPS tracking apps. Geo-location based app development company selects the right tech stack to make your GPS tracking app development successful.

A Step-by-Step Guide To Location Tracking Mobile Apps Development

How to build a GPS tracking app? Or how to create a location-based app? No worries, here is the complete guide to location based app development.

Step-1: Market Research

If you plan to develop location-based mobile apps, do thorough market research to explore hidden opportunities for apps development within the targeted market. Also, get all the information related to competitors and the functionalities of location-tracking apps offered to their audience.

By doing so, you can offer a unique geolocation tracking app with more benefits that are not available to customers in the rival application.

Step-2: Analyze Target Audience

It is the second most important factor to consider while developing location-based mobile applications. Enterprises need to analyze the preferences of people they want to target.

The insights into customer’s choices, needs, and what they are looking for in geolocation apps let you create a resourceful location tracking app for your audience.

Step-3: Right Technology Stack

Selecting the right technologies and tools is essential for GPS-based apps development. A different set of technologies are required for indoor and outdoor navigation apps development. By default, location-tracking apps need Google Maps SDK for both Android and iOS apps development.

If you want to create geolocation tracking apps without using GPS technologies, you can use iBeacon or any wireless network to trace positions and deliver seamless navigation to your audience.

Step-4: Finalize the Features

It is a fact that the set of features and functionalities that you offer through the application will decide the success rate of apps. If an application meets the user’s needs, it will surely hit the app stores shortly.

Before commencing the development stage, we should gather app requirements and choose user-centric features. Geolocation apps mandate map view, location guide through voice, pinning users’ location, route mapping, location-based notifications, location sharing, etc.

A few GPS trackers also need to be included with parking slots tracking facility, upload photo and find locations, and updates on traffic, etc. So, based on your industry and target audience, add the required features to your application.

Step-5: App Design and Prototyping

Mobile app prototyping gives an idea about how your final application looks like. A prototype should reflect User experience and User interface-based view of the application and its working flow between pages.

At this stage, you can also make changes to the design by removing unnecessary app elements, if needed, and streamline the development process.

Designing a visual app prototype will also help in evaluating technical feasibility, improving apps visibility and quality, presenting future app ideas to customers in a clear way, reducing development risks, and many more.

Step-7: Commence Development

The development phase of an application plays important role in the entire location-based Mobile app development life cycle. Once the wireframe design is completed, we can start the development process using agile software development methods.

Generally, the mobile apps development process will take four to six months. But based on the app’s complexity level, the time might cross the boundaries.

Step-8: App Testing

The final step in the software application development process is the testing phase. In this phase, the quality assurance team checks for bugs in the application, if any. App functionality and its performance parameters will also be determined in this stage to deliver an efficient and quick responding mobile application.

Our experienced mobile app testers conduct various app tests to increase its transparency and quality. Let us know your app idea and get a free app quote!

Along with these, choosing the best mobile apps developers is also a tough task for enterprises that are planning to invest in mobile application development. Hiring the right app development partner who has vast experience in the industry benefits you in terms of apps quality and price.

So, we being the leading mobile apps development company in the USA, be it an android-based GPS tracking app or native iOS app development, we suggest businesses scale the platform usage of their targeted audience and invest. This business strategy would help enterprises generate more profits through high app downloads.

Get expert consultation to know the price of location-based mobile apps development.

[contact-form-7]

How Much Does GPS Tracking Cost?

Cost Of Location-based or GPS-based or Wi-Fi/Cellular Networks-enabled Location Tracking Mobile Apps Development

Location based mobile app development is estimated that the development of a location-based app with minimum features will costs around $45,000-60,000 for a single platform.

GPS tracking app development cost will also go beyond $100,000-150,000 if it is integrated with advanced features and has a complex design.

The cost of cross-platform location-tracking service applications with complex app UI and Geofencing functionalities will be around $200K-$280K.

However, location based app development cost might be decided altered on the below factors-

• Geolocation apps features
• Location-based apps UI design complexity
• Location tracking application development platform
• The technology stack used for GPS tracking apps
• Hourly rate of location tracking mobile apps development companies
  • Location-based mobile app development rates in London, UK- $50-99 per hour.
  • Geolocation tracking mobile apps development cost in Boston and Austin, USA is $150-$200 per hour.
  • The hourly rate of location-based service mobile apps development in San Francisco, USA is $100-150.
  • The cost of location-aware applications on android or iPhone operating systems in Canada is $100-150 per hour.
  • Leading mobile app development service providers in Bangalore, India will charge around $25-55 per hour.
• Team size of Mobile Apps Development Company

9 Best GPS Location Tracking Mobile Apps for Android and iOS

1. Google Maps

• GPS Functionality: Navigating locations, getting real-time updates on traffic, exploring destinations, offline maps (to search and navigate without internet connection), and voice-enabled route mapping. Besides, street view and indoor photos of restaurants and more.
• App rating: 4.7/5
• App Downloads: over 50 billion
• App Availability: Android and iOS

 

2. Waze- A GPS Navigation Software

• GPS Functionality: The best GPS tracking app for Android and iOS platforms in 2021. It features live GPS tracking, traffic alerts, and guides through traffic-free routes, plays music from the Waze app, information on estimated destination arrival time, and voice guidance to direct the routes.
• App rating: 4.1/5
• App Downloads: over 100 million
• App Availability: Android and iOS

 

3. Sygic GPS Navigation & Offline Maps

• GPS Functionality: It is the most downloaded and trusted GPS navigation apps in the world. It allows users to find locations and also enables users to store location maps and use them in offline mode.
• App rating: 4.5/5
• App Downloads: over 50 million
• App Availability: Android and iOS

 

4. Life360 

• GPS Functionality: locate family members in real-time, alerts to family members on arrival, maps, real-time location sharing feature
• App rating: 4.5/5
• App Downloads: over 50 million
• App Availability: Android and iOS

 

5. Foursquare City Guide

• GPS Functionality: Traces users’ location, sends personalized recommendations and tips on places, and allows location sharing.
• App rating: 4.2/5
• App Downloads: over 10 million
• App Availability: Android and iOS

 

6. MapFactor Navigator

• GPS Functionality: Voice navigation in various languages, door-to-door routing, visual maps display with distance, guide routes based on vehicle type, updates on live HD traffic information, offline navigation, and many more.
• App rating: 4.6/5
• App Downloads: over 10 million
• App Availability: Android and iOS

 

7. Phone Tracker

• GPS Functionality: accurately locates Kids & tracks phones by number in seconds, sends GPS notifications on kids’ movements.
• App rating: 4.5/5
• App Downloads: over 50 million
• App Availability: Android and iOS

 

8. iSharing- GPS location tracker

• GPS Functionality: tracks locations in real-time, alerts and notifications on arriving destinations, location sharing, and best for tracing stolen phones, etc.
• App rating: 4.5/5
• App Downloads: over 10 million
• App Availability: Android and iOS

 

9. Glympse- Best Location sharing app

• GPS Functionality: GPS tracking, real-time location sharing, sends estimated arrival to others if the users are trapped in traffic.
• App rating: 4.2/5
• App Downloads: over 5 million
• App Availability: Android

 

• Ride with GPS
• GPS Functionality: voice navigation, bike route planner, tracks riding activities, navigates and records upcoming rides, gives feedbacks in real-time, offline maps, Bluetooth sensor support for tracking heart rate while riding, etc.
• App rating: 4.2/5
• App Downloads: one million+
• App Availability: Android and iOS

These are a few GPS trackers used for finding locations and reaching destinations. Now, we will have a look at on-demand service apps that are equipped with location-tracking capabilities.

Would you like to know How much does tracking app cost?

Get in Touch

Trending Instant Service Apps with Location Tracking Capabilities

App Name	App Category
Uber Eats, Swiggy, and Zomato	Online Food Delivery Apps
Airbnb, Skyscanner, and Tripadvisor	Online Travel Booking Apps
Tinder, League, and Bumble	Online Dating Apps
Facebook, WhatsApp, and Snapchat	Online chatting apps or Social Networking apps
Google Fit, Strava GPS, and Map My Fitness Workout Trainer,	Best fitness apps
Google Photos and Explorest	Photo location finders

Future Of Location Tracking Mobile Apps Development

According to the market reports, the location-based services apps are anticipated to grow by $153 billion in the next coming three to four years. Such a growing number will create a competitive landscape for GPS-enabled mobile applications development.

This rapid increase in demand for real-time geolocation tracking apps will ensure bright scope for businesses across retail, transportation, food delivery, E-Commerce, automotive, fitness, etc.

Would you like to know the process of GPS apps development using advanced technologies?

Get in Touch!

[contact-form-7]

 

Wrapping Up

We hope that this article is helpful for those who plan to develop GPS tracking apps or location-based service apps.

GPS tracking or location-based apps for iOS and Android devices are the best digital solutions for users to navigate places, locate assets, track missing kids, and online deliveries.

As location-based apps development is in high market demand, we have already created the best app development approaches and strategies in advance. Such fore planning helps USM create best-in-class location tracking service apps for our customers across retail, banking, healthcare, travel & logistics, and many other industries. As discussed, the cost to develop a location-based app depends on factors that we’ve discussed here.

Do you have a geolocation tracking app idea and looking for a mobile app development partner? Let’s Talk!

[contact-form-7]

Top 5 AI Apps For Speech Recognition

Artificial Intelligence technology has touched almost every aspect of life and the environment. In particular, Speech/Voice recognition is one of the trending technology belonging to AI that made human-to-machine interactions simple and faster.

Voice recognition or speech recognition is gaining popularity around the world. The rise of AI and voice-controlled intelligent assistants have made virtual interactions over a secured platform easier and more convenient. These cutting-edge digital technologies can convert human speech into machine-understandable code and revert back to human spoken language. Google Assistant, Microsoft Cortana, Apple’s Siri, and Amazon’s Alexa are a few best examples of speech recognition apps that have attained huge popularity in the market.

According to market research reports, 74% of smartphone users or digital customers rely on voice-based assistants to search for products and services, open their favorite playlists, make a shopping list, track the mailbox, etc. Such wide acceptance of AI and speech recognition applications is a profitable note for voice recognition technology companies.

It is expected that the global voice recognition apps market is expected to reach $18 billion by the year 2023, at a compound annual growth rate of 23.89%. So, businesses can either integrate AI features in existing apps or start to invest in AI development to grab market opportunities.

Let’s discuss

[contact-form-7]

Whether it’s on a standalone home device or Smartphone, the benefits delivered by digital voice assistants are incredible. Therefore, speech recognition AI will offer unbelievable businesses growth opportunities for organizations. The opportunities of developing AI-powered voice-controlled apps or speech recognition applications has great scope in the future.

Get your free resource:

How AI is Used in Speech Recognition: Top 5 AI Apps for Speech Recognition

#1 Google Assistant- One of the Best AI apps in 2022

Google Assistant is one of the best voice recognition applications. It is a popular speech recognition application developed using AI. This Artificial Intelligence (AI) enabled and voice-powered virtual assistant software. It is known as one of the trending and advanced virtual assistants.

Google has partnered with a number of firms to make Google Assistant available on large number of smart devices such as head phones, smart phones, cars, fridges, etc.

Here, you can learn about what is Google Assistant and how does it work?

Google speech recognition app supports both text and voice entry and uses the latest AI technology like NLP (natural language processing). It provides a variety of services, including voice search, voice commands, assists tasks, translates in real-time, sends reminders, finds information online, makes appointment, and many more.

Google speech recognition app has also expanded its virtual assistant services significantly. It supports 10,000 devices across over 1000 brands.

Also Read: Top 10 Artificial Intelligence Technology Trends In 2022

 

#2 Alexa- Top Speech Recognition AI App

No doubt. Alexa is one of the best voice recognition apps for android and is also recognized as one of the top voice recognition apps for iPhone. Alexa is also known as Amazon Alexa, is an AI-based virtual assistant from the multinational company, Amazon. Initially, it was tried with Amazon Echo dot smart speakers and Amazon Echo. Anyway, currently, it is not available on iOS and Android platforms.

Amazon Alexa uses NLP, voice queries, etc. to provide services like music playback and voice interaction. In addition, it will set up alarms, creates to-do lists, plays audiobooks, and streams podcasts. Moreover, Alexa can also give live information about traffic, the latest news and sports, and the weather which are very useful.

You can experience this virtual assistant on Mac and Windows, and it requires some easy steps to setup. Some PCs accept Alexa’s hands-free activation, while others need you to click the Alexa icon.

#3 Siri – Best AI apps for speech recognition:

Can AI do voice recognition? The best answer is Siri-like famous voice recognition applications. Similar to Alexa and Google speech recognition app, Siri is one of the best AI apps for speech recognition.

Siri is one of the Top 5 AI apps for speech recognition applications which is delivering top-notch performance and assisting iPhone users virtually in many ways. It is a well-known virtual assistant recognized speech software from the Apple Company.

Siri uses Voice Questions and the Natural Language User Interface (UI) to work and send text messages, make calls, answer queries and make recommendations. It assigns requests to many Internet services. Besides, Siri adapts to users’ searches, language, and preferences.

#4 Microsoft – Best AI Voice Recognition Software

The most popular voice recognition apps for android and iOS. Another strong AI application that does not require an introduction is Cortana, a virtual assistant from the tech giant, Microsoft. Cortana provides problem-solving, hands-free assistance, answers queries, performs specific tasks, takes notes, gives reminders, and assists in calendar management. Over time, Microsoft’s Cortana “learns” and performs complex tasks.

Cortana uses information from Bing search engines, NLP, and other devices to provide personalized recommendations, and it consists of a speech API that greatly works with Windows and 3rd party applications.
This voice recognition software is available on iOS, Android, Windows Mobile, Microsoft Band, Windows 10, Windows Mixed Reality (MR), Invoke Smart Speaker, and Xbox One.

You can also see Cortana on famous headsets such as the CloudX, HyperX, Logitech G933, Sennheiser GSP350, and Razor Kraken 7.1 V2.

Recommend To Read: Top 10 AI apps for speech recognition

#5 Hound 

It is one of the top 5 AI Apps for speech recognition. The Hound app, Silicon Valley Company named ‘SoundHound’ has launched this Hound application. This virtual assistant app answers the queries of users and completes several tasks such as calculations and recognizing words correctly in the process with 95% accuracy.

The Hound app can send a text message and make calls for you. You can also have information about weather conditions, breaking news, hotels, and restaurants nears by, call Ola or Uber, check the status of the flight, etc. This digital assists app is available on both iOS and Android.

This best AI voice recognition software app uses its Deep Meaning Understanding and Speech-to-Meaning technologies. Hound has an excellent range of customers, e.g., Honda, Mercedes Benz, Hyundai, and Motorola.

Recommended: Top Artificial intelligence Companies in US, India & Europe

These are the top 5 AI apps developed using speech recognition technology. All apps have been crowned as the best AI apps in 2022. Speech recognition in AI is really a gift for voice recognition technology companies to create miracles with technology. Voice recognition technology companies are assisting businesses across different verticals in creating futuristic speech recognition AI software applications.

Best AI Tools for Speech Recognition in 2025

In 2025, there are various AI speech recognition tools that can accurately and rapidly convert speech into text. Some of the well-known ones are:

• Google Speech-to-Text

An extremely accurate tool that can transcribe speech in real-time and has support for various languages.

• Microsoft Azure Speech Service

A strong speech recognition functionality that includes transcription as well as translation. It will be utilized to develop most of the voice-enabling applications.

• Amazon Transcribe

A cloud service for speech-to-text transcription, ideal for customer call, meeting, or media transcription with multi-accents and language support.

• Deepgram

A speech recognition platform powered by AI that prioritizes high accuracy for business use, with features such as real-time transcriptions and training custom models.

• Rev AI

Highly accurate transcription is what Rev AI is best known for, and it is commonly used to transcribe podcasts, interviews, and videos.

These AI tools for speech recognition in 2025 simplify the process of integrating speech recognition capabilities into products for developers and businesses, making it easier to improve accessibility, customer service, and user engagement.

Cost of Building an AI Voice Generator App

The cost of building an AI voice generator app may be $50,000 to $150,000 based on features, platform, and AI complexity. User interface design, voice generation API integration, and voice processing and storage with cloud infrastructure will also impact the overall cost of developing an AI Voice app.

Further, features such as multi-language integration will increase the final cost of developing an AI text-to-speech app. Moreover, licensing AI models or cloud services, such as AWS or Google Cloud, will also be an additional expense to the estimated cost of building an AI voice generator app.

However, additional costs for developing an AI text-to-speech app can be added for fine-tuning the models to achieve high-quality, natural-sounding voices. Maintenance, server prices, and security features also contribute to the overall cost of developing an AI voice app.

How to Build an AI-Based Language Learning App?

To develop voice recognition apps for iPhone or voice recognition apps for Android, AI development companies follow a precise process to ensure the successful app development.

Firstly, to create an AI-driven language learning app, incorporate AI technologies such as natural language processing (NLP) and speech recognition for customized lessons. Machine learning can adjust content to the skill level of the user. Real-time translation, grammar check, and pronunciation feedback are the highlight features that utilize APIs such as Google Translate or IBM Watson.

Second, develop a backend infrastructure for handling user data and tracking advancement. Secure platforms in the cloud, such as AWS or Firebase, make safe data storage possible. Facilitate privacy compliance and provide offline accessibility for lessons. Integration of social capabilities such as native speaker language exchange makes it a better experience. Periodic updates of content and AI updates will make the app efficient and topical.

Final Words

As per the research reports of Trend force, the voice recognition solutions market across the globe is forecasted to reach USD 15.98 billion by the year 2021. Virtual/ speech recognition is becoming an integral part of AI systems and it gives more communication to users.

Thanks to natural language processing, it is constantly learning from us and making necessary changes in the way we live, and perform. Businesses across the globe are expected to invest more in this speech recognition technology as the whole voice infrastructure improves soon.

Planning to Develop an AI-Powered Speech Recognition App for your Business?

USM Business Systems is providing cutting-edge AI solutions to transform your business. We have a team of experienced and professional AI developers who gained unbelievable hands-on best practices in using various advanced technologies.

Contact us today. We would love to assist you!

Let’s discuss

[contact-form-7]

 

Best Video Streaming Apps In The USA

Online video streaming applications were ruling the global media services and completely altered the way people explore information. Driven by the increasing availability of high-speed internet coupled with the cumulative use of smartphones, the popularity of video streaming apps is on the rise.

According to Statista, the global video streaming application industry has reported $86 billion in 2021 and it is estimated to reach $115 billion by the next coming three years.

In particular, out of the total market value, smartphone users in the US alone are spending nearly $44 billion on premium audio or video streaming applications during the year. Most of the revenues are generated from the US market. Estimates are also showing that video streaming app development in the US will offer a profitable market to investors.

In this article, after doing deep research on the USA’s video streaming industry, we have compiled a list of top video streaming apps in the USA. Be you invest in Netflix clone app development or Disney+ clone app development, or YouTube clone app development, it will create a valueble addition to your media services.

Let’s look at the top 5 video streaming apps in the USA.

The 10 Most Popular Streaming Services

#1. Netflix App- Best On-demand Video Streaming App (Android & iOS)

With over 1,000,000,000+ downloads (just from Google Play Store), Netflix has stood as the number #1 online video streaming app in the world. The app is popularizing in providing uninterrupted live video streaming services to users. Users or paid subscribers can watch TV shows and movies on Netflix.

The app is been preferred by nearly 45% of video streaming app users in the USA. Hence, the development of a Netflix-like mobile app for Android or iOS will help you build brand value and reach more audiences faster.

Features and Functionalities Of Top Online Video Streaming Apps like Netflix 

With the below features, Netflix stood as the top player in the list of streaming media services. These advanced and user-friendly features also made Netflix one of the best native live streaming apps in 2025.

• Hassle-free registration and login
• Get a membership with an existing email Id to access the app’s features
• Watch live TV shows and movies that you love on mobile devices, laptops, or smart TVs
• Users can watch series, documentaries, and stand-up specials of their choice in their native languages
• Users can save their favorites and watch in offline mode anytime
• Safe kids-friendly shows for ensuring family-friendly entertainment
• Push notifications on new episodes and the latest releases 

Key information Of Netflix App – Best Streaming Service for Live TV

• Date of launch:1997
• Headquartered in: California, USA
• Android Rating: 4.5/5
• iPhone Rating: 3.9/5

#2. YouTube- Top Video and Music Streaming App In The USA 

YouTube is one of the biggest online video streaming apps with accessibility to billions of customers across 100 countries in the world.

Over 90% of the internet population is downloading and using this global largest video-sharing platform to stream and watch their favourite videos. This is where it has occupied position as the best video streaming apps USA in 2025. The app also facilitates users to subscribe and share video channels instantly.

 

Top features of YouTube – Video streaming services in USA

• Top on-demand Video Streaming App like YouTube offer simple login
• Custom search functionality to easily find the video content that the users looking for
• High-level authentication for ensuring the security of the user credentials
• The app is compatible to connect external devices and enhance the user experiences
• In-app voice-based search functionality for making the users’ search easier
• Allows users to spread the content and touch with their audience through live video streamlining functionality
• Easy to subscribe to favorite channels and watch the best & latest video content

Key Information

• Date of launch: 2005
• Headquartered in: California, USA
• Android Rating: 4.2/5
• iPhone Rating: 4.7/5 

Recommend to Read: How Much Does IT Cost to Develop YouTube Mobile App?

#3. Disney+ Hotstar- Popular Video Streaming App In The USA 

A video streaming app development like Disney+ will deliver high returns on investment. Disney+ is one of the most popular video streaming apps in the USA. As of records, the app has approximately $150 million subscribers and become one of the top competitors to the Netflix mobile app.

Key features of Disney+ like trending OTT apps in the USA 

• Top OTT video streaming application like Disney+ offers quick login
• Search facility to explore the desired content faster
• Social integrations for accessing the app
• User profile and watch list for better managing the data
• USA’s best video streaming app like Disney+ offers Genre wise content
• Disney+like the most popular video-on-demand over-the-top streaming service allows users to access the video content in their native languages as the app is multilingual
• Push notifications feature to send app updates to the users 

Key Information

• Date of launch: 2019
• Headquartered in: Los Angeles, California, US
• Android Rating: 3.9/5
• iPhone Rating: 4.6/5 

#4. Amazon Prime Video-Famous Video Streaming App in The US 

Amazon Prime Video is one of the other American leading video on-demand OTT streaming service apps with nearly 172 million subscribers in the country.

Best features of Amazon Prime best video movie streaming app

• The app gives access to a range of movies, TV, and sports
• Personalized video content recommendations
• Chromecast feature to broadcast videos from phone to any other supportive devices
• Create or join a watch party feature for chatting while viewing videos
• Pause and resume option for convenient broadcasting and viewing experiences
• Notifications on favorite actresses’ movie releases or any videos
• Download videos online to watch offline 

The cost to develop video streaming apps for TV like Amazon Prime will depend on these features.

Key Information

• Date of launch: 2006
• Headquartered in: Seattle, Washington
• Android Rating: 4.1/5
• iPhone Rating: 4.7/5

#5. Hulu- Most-downloaded Video Streaming Application In The USA

The best on-demand video broadcasting applications like Hulu are on our list of top mobile apps for live video streaming. The app has lifted media entertainment to the next level.

Features and functionalities of the Hulu app – Video streaming services in USA

• User-friendly registration and signup process
• Fast login and secure authentication
• Attractive design for improved user experience
• User profile
• Video Library and watch list
• Availability of video content in different languages
• Custom search for making the user’s search faster
• High-level privacy or lock feature to secure the application
• Sends push notifications about new videos or TV shows
• Personalized video recommendations
• Social media sharing facility
• Reviews and ratings

Key Information

• Date of launch: 2008
• Headquartered in: California, USA
• Android Rating: 4.6/5
• iPhone Rating: 4.6/5

 

How to Develop a Video Streaming App?

For creating the best video streaming apps consider some of the most important steps:

• Define the Concept: Choose the nature of content (live streaming, on-demand, etc.) and users.
• Select the Tech Stack: Choose the programming language (Swift, Kotlin, React Native) and backend services (Node.js, Python).
• Choose the Streaming Protocol: Apply protocols such as HLS (HTTP Live Streaming) or DASH for delivery of the videos.
• Set up Media Storage: Store and distribute videos using cloud services (e.g., AWS S3) or content delivery networks (CDNs).
• Develop Video Player: Integrate or develop a video player to manage streaming, including play, pause, seek, etc.
• Backend Development: Use server-side technologies to implement user authentication, content management, and analytics.
• Create Frontend Interface: Develop and design an easy-to-use user interface with functionalities such as search, categories, and recommendations.
• Test and Optimize: Validate video quality, app performance, and resolve bugs.
• Deploy and Launch: Release the application on app stores or web-based platforms and track user feedback.

How Much Does It Cost To Develop Video Streaming Apps like Amazon Prime Video/YouTube/Netflix/Hulu?

How much does it cost to start streaming apps?

Do you have this question in mind? No worries, we are here.

The estimated cost of video streaming apps will be around $25,000- to $35,000+ for a single platform. The development cost of OTT app development for multiple platforms will be $35,000 to $60,000+ with moderate complexity in design. The live streaming app development cost is based on the complexity you increase.

However, the app development platform, application design, features list, technology stack, app type, and the hourly cost of mobile application development you hire will all impact the cost to build a video streaming app.

Final Words

Amazon Prime Video, YouTube, and Disney+ like video streaming application development would be the best decision to catch up with the market opportunities. Businesses can generate the flow of revenues by developing paid subscription models.

USM is one of the top video-streaming mobile app development companies in the USA. Our team of mobile app developers is an expert in the design and development of Netflix-like trending OTT apps.

Are you looking to hire a top Video Streaming App Development Company in the USA?

 

Get In Touch!

 

[contact-form-7]

Difference Between Artificial Intelligence and Machine Learning

Nowadays, Artificial Intelligence (AI) and Machine learning (ML) technologies are the two most trending technologies. Many companies are investing in AI and ML applications to transform the existing business processes.
Most of the people are confused about the difference between Artificial Intelligence and Machine Learning. So, we are here to clear your confusion!

Today, in this article, we will be giving a detail about what is AI? What is ML? And what is the major difference between AI and ML technologies.

What is Artificial Intelligence (AI)?

Artificial Intelligence is defined as a smart concept that enables machines to perform various tasks done by humans. AI becomes more popular nowadays with its automation and intelligent features.
AI has been in talks since long back. Gradually, the technology is moving to the next level. The researchers continue to invent something new in AI. Artificial Intelligence machines can solve complex calculations.
AI along with ML techniques, it has been scientifically proven to reflect human decision processes and improve machine intelligence.

Get in Touch

[contact-form-7]

How Does AI Works and Why Is AI So Important?

• AI can automate the every task which is done by human previously
• AI frequently performs high-volume machine tasks efficiently
• Industries are improving their tasks using AI capabilities
• AI-based apps, conversational tools, and chatbots help companies in improving digital marketing
• AI can build fraud detection systems to identify and track illegal access to data systems or network
• AI uses ML to predict the future outcomes
• AI apps in healthcare used to detect diseases with high accuracy
• AI in automobile used for developing autonomous cars

The field of Applied AI is still observing advancements. We can state that advancements in AI is welcoming more innovations in ML. As a subset of AI, machine learning program is giving more valuable insights and predictions into data. Thus, ML is supporting new research works in AI.

What is Machine Learning?

The machine learning is best defined as an important application of AI, which allows a computer or machine to learn from input data and improve the experience without the need for explicit programming. The primary aim of the advanced machine learning algorithms is to allow systems to learn automatically without one’s interaction.

Rapid Growth of Machine Learning

Driven by the advancements in AI, the demand for ML techniques is expanding rapidly. ML allows the software to predict future outcomes accurately.

In addition, a vast amount of digital data over the internet is increasing the demand for ML solutions. In particular, digital businesses are highly adopting ML, and deep learning apps to manage their customers proficiently.
The researchers thought that instead of training machines how to perform, it’s better to code them once to do repeated tasks automatically. This trend increased the demand for the development of machine learning, deep learning, data analysis, and predictive analytics.

How Does Machine Learning Works?

How does AI differ from machine learning:

• Step 1: Learns from a trained data set
• Step 2: Identifies dissimilar data from a group of similar data and hence measures error rate
• Step 3: Identifies noise attributes to improve the processing capacity
• Step 4: Data validation and testing processes to deliver accurate error measure
• Step 5: Insights into data

Difference Between AI and Machine Learning: Artificial Intelligence Vs Machine Learning

Here are the top differences between AI and ML:

The above table helps you learn how does AI differ from machine learning. Being a subset of AI, the difference between machine learning and AI is specific to learning and insights extraction.

What is Generative AI?

Generative AI is a form of artificial intelligence that produces original content, such as images, text, or music, based on learning from current data. It utilizes models such as GANs and transformers to create realistic results that mimic actual instances. The technology applies to industries such as art, entertainment, and medicine.

What Is The Difference Between Generative AI And Machine Learning

Both generative AI (GenAI) and machine learning fall under artificial intelligence but have varying uses. Machine learning aims at model training for the purpose of recognizing patterns within data and prediction or decision-making, including categorization of data, predicting trends, or the identification of outliers. Machine learning incorporates methodologies such as supervised, unsupervised, and reinforcement learning.

Generative AI, in contrast, is a niche field of machine learning whose purpose is to generate new content, images, text, or music from given prompts. The major difference between generative AI and Machine Learning is mostly about analysis and prediction.

Another difference between Gen AI and machine learning is in their model training goals. Machine learning models are trained to achieve optimal performance on tasks such as prediction by maximizing accuracy. In contrast, generative AI models are trained so that they will discover the structural and distribution information in the data to produce fresh, related data.

Is ChatGPT AI or Machine Learning

ChatGPT is powered by AI technology that uses machine learning and deep learning to better understand user prompts and create human-like responses. It’s trained on massive amounts of text data to learn about language patterns, context, and structure, enabling it to respond to questions, engage in conversation, and help with other tasks. Although ChatGPT itself uses machine learning, it is a subcategory of the larger AI genre because it demonstrates intelligent behavior such as natural language generation and understanding.

Neural Networks

The primary reason for the development of Neural Networks is to train the systems to replicate exactly like humans.

A Neural Network system can categorize the data in a manner as human brain do. These systems can recognize images and categorize them based on the elements they comprise. In the image below, the nervous system takes an input image, processes it, and finally identifies objects using previously gained experiences.

Based on the trained data, it can make decisions, predictions, and statements with confidence. Along with the feedback loop, it can decide the predicted decisions are wrong or right. Thus, neural network systems can modify the approach it takes in the future.

Accordingly ML apps can read and understand the input text and categorize whether that text is a complaint or greetings. In addition, ML applications can also listen to music and determines whether it makes a person happy or sad.

All these are a few applications of ML and neural network systems. The major idea behind all research works is connecting digital data and electronic devices intelligently. To reach this, AI also uses natural language processing (NLP) to efficiently understand human language.
NLP is highly dependent on ML techniques. The NLP-based apps can interpret written/spoken language and respond to the user in the same way.

Machine Learning Vs Neural Networks

Machine Learning	Neural Networks
Falls under the field of artificial intelligence	A sub-field of machine learning
Enables machines to automatically learn and process input data without being explicitly programmed.	Also called as artificial neural network used for categorizing data/images as our bran do
Types: Supervised and unsupervised learning methods	Types: Convolutional neural networks and recurrent neural networks
Mostly used in healthcare, retail, e-commerce, pricing strategies, customer retention etc.	Applied in finance, healthcare, retail, stock prediction, and etc.
Google Maps, Siri, and google search are the best examples of machine learning.	Image recognition, compression, and search engines are the best examples of neural networks.

Advanced Artificial Intelligence and Machine Learning Market Overview:

Increased investment in AI technologies, the growing need to process large amounts of data and the lack of experienced technicians to manage business tasks are key growth factors of the artificial intelligence market size. In between 2016-2025, the market size is expected to project $169.41 billion by 2025 from $4.06 billion in 2016.

To Conclude, Next-Level of AI and ML Offers Huge Opportunities to Businesses

Despite the difference between AI and ML technologies is being thin, we can understand that the combination of AI and machine learning models provides intelligent business processes. Different industries ranging from healthcare and banking to manufacturing and e-commerce are widening business opportunities. Thus, AI, ML, deep learning, and neural networks expand your brand awareness.

For instance, the sales and marketing teams are using ML systems to detect the behavior of its customers search. Thus, AI & ML apps for marketing and sales industry are providing growth benefits to them. Multiple developments in AI leads to the development of ML technology even more.

Connect with USM to know more the benefits of AI and ML Technologies.
Hope, this article makes you understand the basic difference between AI and ML. We would like to add more valuable information related to Artificial intelligence, reinforcement learning, computer science, data science, big data, and deep learning technologies.

Get in Touch

[contact-form-7]

 

Top 50 AI Companies in USA, India & Europe

List of Best 50 artificial intelligence AI companies in USA, India & Europe

Artificial Intelligence (AI) is broadly expanding in the market. Several AI start-ups and Artificial intelligence initiatives exist in the market.

In this digital era, AI is a significant investment area. Many tech AI companies like Microsoft and Google are heavily investing in AI. It is not limited to those companies, but every business is in plans to modernize with AI.
According to a survey conducted by The New York Times, 50 AI firms are playing a vital role in shaping the future with AI. Along with AI, these companies are benefiting with machine learning, deep learning, data science, speech recognition, and other AI technologies.

Recommend: What is artificial intelligence & how it brought revolution?

USM Business Systems – Expert In Custom AI & Mobile App Development Solutions
Location: Chantilly (Headquarters), VA, United States
Founders: Madan Kalakuntla

USM is the global leading artificial intelligence company based in Chantilly, United States. With our specialization using artificial intelligence and machine learning technologies, we fuel our client business with emerging AI solutions.

Our AI experts aim to develop and deliver result oriented and customer centric AI-driven mobility solutions for various businesses across diversified industries. We primarily deliver AI services to Banking and finance, healthcare, manufacturing, retail, e-commerce, telecom, marketing and sales, and education sectors.

We captured a strong brand name as the best Artificial Intelligence (AI) Services and Solutions provider across Virginia, California, New York, Illinois, Texas, Florida, Washington, and other states of the United States. Accordingly, we also have a strong footprint in European, Middle Eastern and other global emerging markets.

Related Services:
1) AI Services and Solutions 
2) Mobile Application Development
3) Workforce Management
4) Cloud Management
5) HR Management
6) Machine Learning
7) Chatbot App development

Let’s drive in into the list top 50 Artificial Intelligence & Machine Learning companies that are a step forward in the AI industry. Want to talk to us get in touch with us for a quick 30 min demo on your AI requirements that your company was looking for.

Get your free resource here:

 

List of AI Companies: 50 Best Artificial intelligence Companies in US, India & Europe

Are you looking for AI consulting companies or AI development companies? Here is the list of AI companies in the USA.

#1 AEye

Location: Pleasanton, California
AEye is a leading AI app company in Pleasanton, California. Being one of the top AI development companies in the USA, it develops vision algorithms, software, and hardware to guide and control self-driving cars. It developed an efficient LiDAR technology. This technology focuses on relevant data in vehicle’s view like people, other autonomous vehicles or animals, etc. It puts less focus on buildings, sky, plants, etc.

I Conclude: Artificial Intelligence in the automobile industry has a great impact on the industry. Starting with driverless cars, taxis, buses, and trucks to robots that work on the factory floor, AI technology has transformed the automotive industry completely.

Recommend: How Automotive Industry Is Evolving With Artificial Intelligence?

#2 AIBrain

Location: Menlo Park, California
AIBrain is a leading artificial intelligence company in California. The company has been ranked as one of the top 10 AI development companies in the USA. It is engaged in developing AI solutions for applications like robotics and smartphones. The company has developed AICore (an AI agent), iRSP (robot software platform), Futurable (AI-based game). AIBrain strives to develop AI products that are autonomous and can solve complex issues and learn from experience. The company is developing Conversational Artificial Intelligence Applications for Children and Adults.

#3 AlphaSense

Location: New York, NY

AlphaSense is one of the top AI development companies for banking and finance and Fortune 500 companies. Using AI technology, AlphaSense can find data on companies, SEC filings, earnings, and recent news from millions of research documents within seconds. It can extend keyword searches to find suitable content that helps clients.

I Conclude:
The use of Artificial intelligence in banking and finance is rapidly growing. Though AI in banking has been sounding for decades, now it is spreading its arms in the industry. Artificial intelligence applications in finance and AI devices in banking are completely transforming the way of operations in the sector. From bringing automation in processes and AI Chatbot applications in banking to data analysis, risk management, and improved personalization, AI is very much useful for bankers and financial institutions.

USM offers AI-powered mobility solutions and services the for banking and finance industries. To know more out our AI-based banking use cases, just click on the below link-

Recommend: AI in Banking: Top Use Cases of Artificial Intelligence in Banking Sector

#4 Amazon

Location: Seattle, City in Washington
Amazon is one of the top 10 AI development companies. It offers various AI products for both consumers and businesses. Amazon Echo is one of its best AI applications. It is a smart speaker that connects to Alexa (An intelligent voice server). This AI device allows you to play music, set alarms and timers, answer questions, and control other smart home devices instantly.

#5 Anki

Location: San Francisco, California
Anki is an artificial intelligence startup based in California, USA. This evolving AI Company is completely focused on bringing robotics into daily life. Being one of the leading AI agencies in USA, It developed two innovative AI products including Cozmo and Anki Overdrive. Cozmo is the top robot of Anki. This product is the most matured consumer AI robots. It can give emotional responses. Overdrive is a complete car racing game with a track.

#6 Blue River Technology Inc.

Location: Sunnyvale, CA, USA
The US-based Artificial intelligence Company builds smart farm technologies by combining computer vision and Artificial intelligence. For instance, its See & Spray technology can develop smart agricultural equipment.
It can identify individual plants and apply herbicide to the weeds. This lessens the number of chemicals by near about 90% over previous traditional techniques. This will yield healthy crops and reduce the number of chemicals sprayed on crops.

I Conclude: Artificial intelligence technology is helping the agriculture sector in boosting yields. Accordingly, AI in agriculture helps to reduce environmental impacts on crops. Nowadays, approximately 40%-50% of startups in the agriculture sector are using AI solutions and methods to improve production.

The below are the top three applications of AI in agriculture industry:

Agricultural Robots: These AI-powered robots can harvest crops faster than humans can.
Weather Monitoring: AI accurately monitors weather conditions and predict future environmental impacts on crops.
Soil Monitoring: Using ML and deep learning techniques, AI-powered devices monitor soil conditions.

#7 Casetext

Location: California, United States
Founders: Jake Heller, Pablo Arredondo
Casetext is an AI-based legal search engine specialized in legal documents, with a database of over 10 million laws and regulations. This CARA A.I. legal research platform can finish the search in approximately 25% faster than other platforms. A recent study comparing legal research platforms found that attorneys using Casetext’s CARA A.I. finished their research 24.5% faster.

#8 CognitiveScale

Location: Austin, Texas, USA
Founders: Matt Sanchez
CognitiveScale is a Texas-based artificial intelligence company. It is one of the top healthcare ai companies in the USA. The company is engaged in the design and development of the best AI app applications for various industries like healthcare, banking and finance, and E-commerce. It is also popularized as one of the best healthcare AI companies in the USA.

Its innovative products are developed using its core Cortex augmented intelligence platform. It helps companies to design, develop, deliver, and manage enterprise level AI systems. It also offers an online AI-powered collaboration system for experts, data scientists, and app developers to solve their issues.

#9 Clarifai

Location: New York, NY
Founders: Matthew Zeiler
Clarifai Inc. is a New York-based Artificial Intelligence Company. It specialized in computer vision and utilizes machine learning and deep neural networks for finding and analyzing images and videos. It helps users to organize, filter, and search their required image database. Clarifai’s advanced AI-powered computer vision solutions unlock the potential of a vast database and accurately finds similarities in images.

#10 CloudMinds

Location: Santa Clara, California, USA
Founders:  Bill Huang, Robert Zhang
It is one of the largest AI firms in USA. This Artificial Intelligence Company is an expert in advancing Human Augmented Robotics Intelligence (HARI) platform. CloudMinds creates, develops, and operates Cloud Robots. It connects Cloud AI to a wide network of service robots and smart devices.

I conclude: AI in Manufacturing: Usage of smart robots in manufacturing that embedded with AI, cloud, and the IoT are improving productivity and automating entire processes. Accordingly, the adoption of artificial intelligence apps and tools in manufacturing is also growing rapidly. With a belief that AI apps bring innovation in manufacturing processes, manufacturers are heavily investing in AI technology.

Hope, this is an incredible AI companies list. AI agencies in USA are helping organizations stay ahead in the digital competition.

Want to know the AI app development cost? Get in Touch with Us

[contact-form-7]

#11 DataRobot, Inc.

Location: Boston, MA
DataRobot’s innovative AI-based platform helps data scientists to develop machine learning models. It uses Machine Learning (ML) techniques, hence the users can build and run predictive approaches without any knowledge of ML and its related programming languages.

#12 DataVisor

Location: California, USA
Using ML techniques, DataVisor’s AI platform can identify fraudulent acts efficiently. It uses unsupervised ML techniques to detect malware before they damage data systems/networks. Especially, DataVisor helps banking clients to protect from various attacks such as fraud transactions, fake accounts, and many more financial attacks.
USM has a strong experience in developing Ai-powered mobile apps for banking customers. Our experts are specialized in using AI and ML techniques to detect irregular patterns of customers’ data. Thus, USM’s AI solutions for banking service providers help to identify and avoid fraudulent acts in a seamless manner.

#13 DeepMind

Location: London, United Kingdom
DeepMind is a UK-based artificial intelligence company. It was acquired by Google in 2014. The company is focused on developing innovative artificial intelligence systems that cover everything ranging from finance to healthcare. Currently, it has AI research centers in Canada, France, and the United States.

I conclude: Here, I would like to discuss artificial intelligence in the healthcare industry. Though being adopted by many sectors, AI uses in the healthcare industry are huge. Improved diagnostics and patient outcomes, minimal- invasive surgeries with AI robots, nursing assistants, remote treatments, etc are ensured using AI in the healthcare industry.

Know more about “5 Powerful Use Cases That Show The Significance Of AI In Healthcare”.

#14 Freenome

Location: South San Francisco, California, United States
Freenome utilizes AI technologies to detect the symptoms of cancer in the early stages. It helps healthcare service providers to conduct diagnostic tests that predict cancer easily. Freenome’s AI platform uses non invasive blood tests for recognizing related patterns of the disease.

I conclude: AI (in healthcare), together with machine learning is assisting physicians to predict the probability of cancer disease in the future. ML helps doctors to identify cancer disease and provide treatment at the right time.
Still, research work is ongoing to produce more efficient ML methods that diagnose various types of cancers in the early stages.

USM Business Systems with its expertise in using AI is providing the best artificial intelligence healthcare solutions to global clients. Know more about what type of AI services and solutions we provide to healthcare clients?

Recommend: Top Eight (8) Ways Machine Learning Is Redefining Healthcare

#15 Google

Location: California, United States
Google is a leader in developing Artificial Intelligence platforms. It was acquired 12 AI startups in four years. Google is investing heavily in AI to gain from the benefits of advanced AI capabilities. Instead of marketing its products, Google’s AI platform always focuses on improving its AI services. The company has two significant AI projects, including TensorFlow and Tensor AI chip.

#16 Graphcore

Location: Bristol, United Kingdom
Graphcore’s Intelligent Processing Unit (IPU) is specially designed to build AI-powered machines. The exclusive architecture of IPU allows developers to run ML models faster and improve productivity. The company is striving to accelerate ML and artificial intelligence applications to make machines intelligent.

#17 H2O.ai

H2O.ai is one of the leaders in Artificial Intelligence. The company’s powerful ML platforms and AI solutions are used by half of the Fortune 500 companies and trusted by over 18,000 organizations and thousands of data scientists worldwide. H2O.ai aimed at transforming every company as an AI company.

#18 IBM

Location: Armonk, NY, United States
IBM is the leader in developing Artificial Intelligence products and AI in solutions. Nowadays, its efforts are moving around IBM Watson. It developed an AI-based cognitive service, AI software as a Service, and scale-out systems to deliver cloud-based analytics and various AI services. IBM purchased three AI startups recently.

#19 iCarbonX

Location: Shenzhen, China
iCarbonX is a Chinese biotech startup. It uses AI technologies to offer health analyses and health index predictions. iCarbonX is an alliance formed with seven global tech companies. These companies collect vast healthcare data.
The company’s AI platform can analyze physiological, genomic, and behavioral information. Thus, this company provides customized medical and health advice.

Recommend: The Significance Of AI Technology By Industry

#20 Intel

Location: Santa Clara, CA, United States
Intel is a United States AI company focused on building Artificial Intelligence initiatives for both software and hardware purposes. Intel’s has developed two processors including Nervana processor (based on deep learning), and Movidius processor (based on neural network & visual recognition). The company also uses natural language processing technologies to introduce new and innovative AI products.

I Conclude: Many AI companies are focusing on developing Ai products using the capabilities of natural language processing techniques.

Know more about NLP : Brief of natural language processing technology
As it enables the machines to understand the human natural language, it is widely adopting by three major industries including healthcare, financial services, and legal.

• Top NLP Use Cases in Healthcare
• To analyze medical records and identify correlations between diagnosis, prescriptions, and treatments
• To maintain quality care
• To provide insights into patient data and gives predicts risks
• Top NLP uses cases in Finance Sector
• Credit scoring applications
• Document search for business intelligence
• Sentiment analysis for providing improved customer service

How Much Does it Cost to Develop AI app development? Get in Touch with Us

[contact-form-7]

#21 Iris.ai

Location: Oslo, Norway
Iris.ai helps scientists to get vital data that supports their research work. Using Natural Language Processing to review huge collections of research papers, Iris.ai platform can find the right documents, extract key data.
Since its introduction, over 120,000 scientists are using Iris.ai Neural Topic Modelling solutions. Recently, the company has released Iris.ai 4.0. It helps users to refine and collect a list of research literature. Thus, this Artificial Intelligence platform reduces manual efforts and gives valuable progress.

#22 Lobster

Lobster is an AI-based platform. It aids advertisers, brands, and media to find and authorize user generated social media content. Using AI and ML Algorithms, it scans multiple social media channels and clouds to find the most relevant content. Then, accurate images or videos will be delivered to the clients.

Recommended: List of Mobile App Development Companies USA

#23 Microsoft

Location: Redmond, Washington, United States
Microsoft deals with consumer oriented and business AI projects. The Cortana is the best digital assistant designed for consumers. This AI products are available on both windows and smartphone. Through its Azure cloud service, the company is offering AI services to businesses. The company is providing bot services, Machine learning services, and cognitive services.

I Conclude: Mobile and web-based digital assistants are performing and delivering results exactly like humans. Top 16 AI-powered personal assistants that understand voice commands and respond to your queries.

• Google Assistant
• Siri
• Amazon Echo
• BlackBerry Assistant
• Jibo
• Google now
• Cortana
• Hey Athena
• Viv
• Mycroft
• Cubic
• Nina
• Vlingo
• Maluuba
• Bixby
• Hound

#24 Narrative Science

Location: Chicago, Illinois, United States
Narrative Science is the United States leading Technology Company specialized in providing artificial intelligence solutions. It builds natural language generation technology to convert data into stories. In general, the data will be collected from many silos. AI focuses only on the most interesting and relevant data to transform data into valuable reports. In addition, it also transforms statistics into stories and numbers into knowledge.

#25 Nauto

Location: Palo Alto, CA, United States
Nauto is an AI-based technology used to enhance the safety of the commercial fleet. Also, it improves the safety patterns of autonomous cars by evaluating the integration process amid drivers, vehicles, and roads. This AI platform avoids accidents and ensures safe driving.

I Conclude: AI in the travel industry: The travel industry always needs the help of advanced technology to improve safety patterns and avoid unexpected accidents. Know more about How Artificial intelligence apps transforming the travel industry.

#26 Neurala

Location: Boston, MA, United States
Neurala’s Neurala Brain makes phones, cameras, and drones smarter. This deep learning neural network software is easy to use. The Neurala Brain uses low-power video and audio inputs to convert simple devices into more intelligent ones.

#27 Next IT Corporation

Location: Spokane Valley, Washington, United States
Next IT is a part of Verint. Verint is one of the leading companies in developing AI-powered customer service chatbots. The company builds conversational AI tools that engage customers with confidence. The company’s Alme platform enables natural language business products to evaluate customer satisfaction and overall performance.

#28 Nvidia

Location: Santa Clara, CA, United States
Nvidia is a leading artificial intelligence company based in Santa Clara, California, USA. Its CUDA GPU Programming language is gaining momentum in the market. In self-driving cars, Nvidia is putting great efforts.

#29 One Model Inc.

Location: Austin, London, Brisbane
OneModel is the best AI Company that helps Human Resource (HR) teams to manage and examine all of the data in an integrated way. The company’s AI-powered HR solutions help the HR department to bring their employees like recruiting, successions, engagement, payrolls, exits, and all others in a single uniform path.

I Conclude: Artificial intelligence HR: Artificial intelligence applications are meeting the needs of various recruiting and hiring needs. AI apps are easing the jobs of human resource departments. From searching and selecting candidate profiles to scheduling interviews, screening, and hiring, every job of the HR team can be automated using AI tools and applications.

Recommend: How Artificial Intelligence Meets HR Requirements?

#30 OpenAI

Location: San Francisco, California, United States
OpenAI is the United States-based non-profit Artificial Intelligence Research Company. It allows researchers and institutions to work together, and permits scientists to enable patents and the research work open to the public.

Want to know the Cost to Develop AI app development ? Get in Touch with Us

[contact-form-7]

#31 Orbital Insight

Location: Palo Alto, California
Orbital Insights is one of the best California based AI Company. It uses Artificial intelligence and satellite geospatial images to get insights that are invisible to the eye. The company uses information from IoT-based drones, satellites, and other aircraft to generate insights for agricultural and energy industries.

#32 Phrasee Ltd.

Location: San Francisco, CA, United States of America
Phrasee is specialized in using natural language generation technologies for marketing.
Phrasee is an AI-powered copywriting technology that uses email subject lines as a language laboratory. Later, verbal elements combine to discover a language model that’s tailored to the brand. Then, the AI technology will be applied to the brand unique language model across all marketing campaigns ranging from email to push, social to display, paid search to the web.

#33 Pointr

Location: London, United Kingdom
Pointr is specialized in indoor positioning and navigation enterprise with analytics features. It enables individuals to navigate busy locations such as stations and airports. Its modules comprise contextual notifications, indoor navigation, location based analytics, and location tracking. In addition, its Bluetook beacons use customer phones to help position them around the building.

#34 Salesforce

Location: San Francisco, CA, United States
Salesforce continues to expand its AI services through acquisition strategies. It has 100% ownership rights in three AI companies. Recently, the company has announced its new Salesforce Einstein AI service. This new initiative involves a group of 175 data scientists. Using ML algorithms, Salesforce helps employees to perform tasks efficiently. In addition, Salesforce Einstein is available for clients who able to build their own AI applications.

#35 SenSat

Location: London and San Francisco, United States
SenSat generates digital copies of physical environments. It applies artificial intelligence models to recognize the various parameters of that environment and give feedback. For instance, it enables infrastructure companies to analyze their environments quickly and provide statistical analysis about a road that is about to undergo repair work.

#36 Sherpa.ai

It is the best artificial intelligence company. Sherpa’s virtual personal assistant app for iOS and Android learns from the user and predicts their needs before they ask. Sherpa works with a range of consumer devices and things that are intelligent.

Recommend: Top 13 Artificial Intelligence Apps for iOS and Android

#37 Siemens

Location: Munich, Germany
Siemens mainly focuses on different sectors like digitization, automation, and energy efficient AI platforms. It is a leading company in providing smart devices and AI systems for power generation and transmission and medical diagnosis.

#38 Sift Science

Location: San Francisco, California, United States
Sift Science offers several fraud management services in a single AI platform. The company uses multiple data points from the web to train and detect fraud patterns.

#39 Tamr Inc.

Location: Cambridge, Massachusetts
Founders: Andy Palmer, Ihab Ilyas, Mike Stonebraker
Tamr is a leading data management service company that simplifies the data unification process. Its services are very scalable, low-cost, and accessible to any industry. It uses Artificial Intelligence to integrate data quickly and efficiently.

#40 Tempus

Location: Chicago, Illinois, USA
Founders: Eric Lefkofsky
Tempus is an emerging AI technology company with a focus on completely removing cancer. Using the power of artificial intelligence, it enables physicians to make real-time and data-driven decisions. Thus, its AI services ensure personalized patient care and optimized therapeutic options for patients through distinctive solution sets.
Best AI companies that work for modernizing healthcare sector.

Know More @
Recommended to read: Startups That Modernize the Healthcare Sector with AI

Want to know the Cost to Develop AI app development ? Get in Touch with Us

[contact-form-7]

#41 Tencent

Location: Shenzhen, China
Founders: Ma Huateng, Zhang Zhidong, Chen Yidan, Xu Chenye, Zeng Liqing
Tencent is a China-based social media company. Recently, they started an Artificial intelligence laboratory. It develops tools to process data across its network, including natural language processing, facial recognition, and news aggregators. In addition, they also have top video streaming platforms called Tencent Music.

Recommend: The Future of Artificial Intelligence in Social Media Marketing

#42 Twilio

Location: San Francisco, CA, USA
Founders: Evan Cooke, Jeff Lawson, John Wolthuis
Twilio is a cloud-based Platform as a Service (PaaS) company. It allows developers to combine audio and video calls and messages into intelligent apps using different APIs.

#43. ViSenze

Location: United States, China, Ireland, and Singapore
Founders: Oliver Tan, Tat-Seng Chua, Roger Yuen, Li Guangda
ViSenze is the best artificial intelligence company. The company is offering artificial intelligence based visual search and image recognition solutions. These AI solutions help online retailers to efficiently engage their clients, improve conversion rates, and boost sales. Like ViSenze, USM Business Systems is also engaged in delivering Artificial Intelligence solutions and services for both online and offline retailers. Our AI-powered mobile apps help you generate more leads. Know more about Artificial Intelligence Services & Solutions

#44 X.ai

The company is develops developed a visual assistant, AMY. It helps the users to manage their scheduled meetings. For instance, in case you received a meeting request, but don’t have enough time to manage timings, copy AMY onto the email, and then she only handles everything. With the help of machine learning and natural language processing techniques, AMY schedules the best location and time for your meeting based upon your provided preferences and schedule.

#45 Zebra Medical Vision

Location: Israel
Founders: Elad Benjamin, Eyal Gura, Eyal Toledano
Zebra Medical Vision strives to transform patient care using the power of artificial intelligence. It is an Israel based company that uses deep learning for radiology. Using many medical images, Zebra Medical Systems can accurately predict diseases.

Recommended: Top 10 Retail E-commerce App Development Companies In USA

#46 H20.ai

H2O.ai is located in Moutain View, California, USA. The company is the developer of H2O, an open source platform for machine learning and data science, used by hundreds of companies around the world.
This firm supplies organizations with machine learning and predictive analytics tools from several industries that help solve complex business challenges.

#47 Vicarious

Vicarious develop Artificial General Intelligence (AGI) robots which are based on the computational concepts of the human beings brain. The organization, which ultimately has a mission to build machines that simplifies the tasks of human. Located in San Francisco, California, Vicarious has associated with the famous tech titans such as Elon Musk, Jeff Bezos, and Mark Zuckerberg.

#48 SoundHound

Soundhound Inc. is located in Santa Clara, California and is completely about audio. It offers a wide range of solutions that uses speech and voice intelligence. The firm’s namesake product will allow customers to recognize songs, plays music and amazingly, answer music-based questions.

#49 Zimmergen

California based popular AI company called ‘Zimmergen’ is using automation, genetics, and machine learning to accelerate the progress of science. The company, which spans the agriculture, chemical industries and pharmaceutical, allows microbes to proliferate through automation software and a massive inventory of digital and physical DNA data.

#50 Zoox

Zoox was established Foster City, California in July 2014. Zook is developing advanced mobility solutions to support urban areas requirements. The organization, which builds their vehicles from the ground rather than fitting technology to existing cars, currently owns self-driving cars throughout the San Francisco area.

Conclusion

These are a few of the global largest AI companies. Now, it’s your turn. Start investing in Artificial Intelligence and transform your business into this advanced technology.

At USM, with vast experience and best practices on using AI and its technologies, deliver high-level AI apps and solutions. Let us know your business need, we get back to you today. Connect now!

Get in Touch with Us

[contact-form-7]

How Much Does Stock Trading App Development Cost?

Fintech has revolutionized the way people trade their stocks. The stocks can now be traded even more easily than before. There are many apps created for trading stocks and options in the stock market. Investors can now trade, monitor trends in the stock market, or manage their portfolios directly from their cell phones. Where there is demand, however, development of stock trading apps would be a great strategy. In this blog, we will discuss the development cost of a stock trading application, current trends that arise, and some of the essential features and technologies involved in the development process.

Current Top Trends in Stock Trading App Development

1. AI and Machine Learning Rise

The role of Artificial Intelligence (AI) and machine learning is becoming increasingly significant in the stock trading apps. These technologies help to analyze vast data providing personalized investment advice, predictive analytics, and automated trading options.

Stock trading apps are becoming prominent in AI and machine learning. These technologies will allow analysis of large volumes of data and much more to contribute to the realm of investment advice, analytics, and automated trading capabilities.

2. Social Trading Features

Social trading has grown within the platform because one can simply follow and copy the trades of other good investors. These systems tend to be community-based and encourage novices to start trading with the platform.

3. Integration with Cryptocurrencies

As cryptocurrencies become more mainstream, trading applications are jumping into the fray by including digital assets. In addition to traditional trading of stocks, giving a better user base to apps to use them for cryptocurrencies would also be good.

4. Enhanced Security Features

With growing data breaches, they have been developing features more related to security enhancement, like two-factor authentication (2FA), biometric login, and end-to-end encryption.

5. Robo-Advisory Services

Robo-advisors offer automated, algorithm-driven financial planning services with minimal human intervention. They can be used for better portfolio diversification by risk tolerance levels and investment purposes.

Essential Features of Stock Trading Apps

While developing a stock trading application, there should be features that bring comfort and functionality to its use. These are some essential features:

1. User Registration and Profile Management

The onboarding process of the stock trading app has to be as smooth as possible. It should make it easy for users to create an account, manage profiles, and set customizable preferences.

2. Real-Time Market Data

Financial news that keeps a user connected with actual time stock prices and market trends is very important for traders. It can keep users informed through the integration of APIs providing real-time data feeds.

3. Order Execution

The heart of any trading app is that it lets users place trades. This includes such functions as: Trades, opportunities, and being able to see order history.

4. Portfolio Management

Users should be able to follow and manage their investment portfolio. This includes performance tracking, tracking profits and losses, and obtaining diversification insights.

5. Charts and Analytics Tools

Advanced charting and analytics implementation enables users to make trading decisions. Technical indicators, bar charts, and historical data are some of the features that are involved in this implementation.

6. Notifications and Alerts

There is push notification for changes in prices, news from the stock market, and order executions, which keep the user noticed and engaged with his investments.

7. Payment Integration

Deposits and withdrawals should always be assured to pass through secure payment gateways. Various payment options such as credit/debit card, bank transfer, and even digital wallets make it easier for users.

8. Customer Support

In-app customer support through AI chatbots or live agents helps in answering the questions of users promptly and increases user satisfaction in general.

9. Educational Resources

Educational content, such as articles, videos, and webinars, can prove useful in helping users gain the maximum out of their trading capabilities and knowledge.

Technologies Used in Stock Trading App Development

The making of a stock trading app consists of all the technologies that have to be amalgamated in order to provide functionality, security, and user engagement. These include the following primary technologies that will be mainly used during the course,

1. Frontend Development

The user interface is fundamental to the engagement of the end-user. Following are the quite commonly used technologies for frontend development:

• React Native: Used for cross-platform app building.
• Flutter: This is another framework for making natively compiled applications for mobile, web, and desktop in a single codebase.
• HTML/CSS/JavaScript: For developing web applications.

2. Backend Development

Back-end takes care of processing data and executing trades. The most used are:

• Node.js: For developing scalable network applications.
  • Python: Becoming very popular because of simplicity and libraries, especially in finance.
  • Java: It is a reliable and scalable technology at the enterprise level.

3. Database Management

User data, transaction history, and real-time market data need a very high-performance database to be stored in. There are several, but among the most common are:

• Mongo DB: NoSQL database. Flexible.
• MySQL: Traditional relational database. Strong data integrity

4. APIs (Application Program Interface)

There are various APIs that should be included in your application to give functionalities like real-time data feeds, payment processing, and trading capabilities. Some of the most extremely common ones are:

• Alpha Vantage: Stock and crypto data.
  • Plaid: User bank account, safe end.
  •Stripe or PayPal: To process payments.

5. Security Protocols

The safety of user’s details and transactions is essential. The following technologies should be in use:

• OAuth: This is authorization with safety.
• SSL/TLS: This encrypts information being sent over the internet.
• Blockchain: This is implemented to add security in transactions, as well as the integrity of data.

Stock Trading App Development Cost

The cost of developing a stock trading app is quite variable, based on several factors, such as the features developed, platform, complexity, and geolocation of the app development company. So here is a list of the factors on which the cost influences the development process:

1. App Complexity

• Basic Apps: These might include basic abilities, including user registration, minimal trading functions, and portfolio management capabilities. Prices may be in between $ 30,000 – $ 50,000.
• Mid-Level Apps: Features installed will comprise real-time data, analytics, and payments. Development cost range from $50,000 to $150,000.
• Advanced Apps: This comprises features such as social trading, AI analytics, and robo-advisory services. Costs can reach up to $150,000 to $300,000 or more.

2. App Development Platform Choice

• iOS vs. Android: Creating your app for both platforms will triple the cost. However, creating it using cross-platform frameworks such as React Native or Flutter helps save some of the costs involved.

3. Location of the Development Team

The location of your development team can significantly affect the cost. Let’s do a rough estimate here:

• North America: $150 to $250 per hour.
• Western Europe: $100 to $200 per hour.
• Eastern Europe: $30 to $100 per hour.
• India and Asia: $20 to $80 an hour.

4. Maintenance and Updates

There will be an ongoing cost after launch for maintenance. Allocate 15-20% of the initial development budget as annual updates and support.

Conclusion

The demand for stock trading apps continues to grow as technology and consumer expectations evolve. Understanding the trends, essential features, and technologies involved in development will help businesses create successful applications. The cost of development of stock apps can vary widely based on complexity, platform, and location, so careful planning and budgeting are essential. By investing in a well-designed, feature-rich trading app, you can tap into the lucrative fintech market and provide users with a valuable tool for managing their investments.

[contact-form-7]

7 Best Mobile Banking Apps In The USA

Mobile banking apps provide customers with 24/7 access to view their account balances and past transactions. Due to the flexibility in accessing and convenience of using mobile banking apps, they are grabbing user attention across the world. Unlike traditional bank deposits by standing in a long queue, digital banking apps are helping users to send or receive money instantly through their mobile devices.

Brand finance companies worldwide are going digital to seize market opportunities and provide more personalized banking services to their customers. In this article, we would like to discuss a list of mobile banking apps in USA. These leading banking apps in the U.S. have higher downloads and usage percentages.

Best Mobile Banking Apps in USA 2025: What’s Going?

Mobile banking apps are the fastest-growing app category in the United States. Almost 90% of banks in the USA are going digital to provide fast and contactless banking services to customers in this pandemic situation. It has become a driver for the increasing adoption and usage of mobile banking apps in the USA.

Due to COVID-19, installations and usage of banking and finance apps have been flourishing since 2019. According to market research reports, downloads and registrations of digital banking applications in the United States increased by nearly 60% during the past year. Here are the significant reasons behind the growth in banking apps downloads in the country.

As depicted in the pie chart, the most common reason to install and use a mobile banking app in the United States in 2020 was to check account balances. Approximately 90% of smartphone users are downloading banking applications to check their account balances on the go.

Followed the convenience of banking apps to view transaction history, remit money, and credit bill payments, the other significant reasons for a surprising hike in app installations in the USA.

A noteworthy point is that the demand for Android or iPhone banking apps in the USA is from people between 25 to 44 years of age. The below figure depicts the growth of mobile banking applications in the USA from younger generations and millennials.

Recommend To Read: Top 10 Use Cases Of AI In The Banking Sector

So, these usage trends are ensuring a profitable and appreciable way for banking app development in the USA during the coronavirus pandemic. In the context of the COVID-19 pandemic, the development of virtual or digital banking apps for Android and iOS in the USA, like those in COVID-impacted countries, will allow people to manage their finances through mobiles without visiting a physical bank branch for their needs.

If you are looking ahead to mobile app development services in the USA, get the best price from us. Contact Now!

Here is the top list of mobile banking apps in the USA, and you can confidently create a clone of any one of the below-listed mobile applications to catch up with the digital market opportunities in the country.

 

The Most Popular Mobile Banking Apps In The United States

If you would like to know more about the best mobile banking apps in USA 2025, we are here to help you out. Below you can find the list of best mobile banking apps for iPhone as well as the best mobile banking apps in USA for Android. Let us take a look at the best 7 out of the top 10 banking apps in USA:

#1. Chime-Most downloaded banking app in the USA

Chime is the best banking app in the USA. It has over 10 million user downloads from app stores yet. Driven by user-friendly features like Touch ID, face ID, a two-way authentication process, fee-free overdraft up to $200, early paycheck clearance, zero maintenance fees, and instant transaction alerts, this app is listed as the most trusted banking application in the USA. The app is compatible with both Android and iPhone banking apps.

#2. Bank Of America Mobile Banking- Most used banking app in the USA

The Bank of America mobile banking app is one of the best mobile banking apps in USA for Android and iOS. This top banking application in the USA has a 4.6+ app rating and 10,000,000+ installs. This digital banking app allows users to deposit cheques, view credit scores, set up custom transaction alerts, e-bill payments, set up travel notifications, and overall organize accounts and loans digitally. It is also popular with its guaranteed cashback offers with BankAmeriDeals®.

#3. Acorns- Highly downloaded banking apps in the United States 

It has acquired the top position in the list of mobile banking apps in USA. Acorns is an American leading banking and also a top FinTech services app. The significant advantages of Acorns-like popular mobile banking applications are easy to check personal and investment account details, the flexibility of direct deposit and mobile check deposit, transaction tracking and history viewing facilities, and high-level authentication processes for fraud detection and prevention.

#4. Current- A famous mobile banking app in the United States

Current is an on-demand mobile banking application in the USA. This leading banking apps in the U.S is available for both Android and iOS users. The benefits of Current-like banking app development in the USA is fee-free overdrafts up to $100, cheque deposits using a mobile camera, insights into money sending, support for Google Pay, Touch ID and Face ID security controls, and many more. Further, the app also allows users to get notifications on bill payments, instant money transfers, and content related to budget management strategies.

#5. Varo Bank- Popular banking app with a high usage rate

It is a popular iPhone banking apps for customers in the USA. Varo is a famous mobile banking app in the United States of America (USA) that runs seamlessly on Android and iPhone/iOS mobile devices. The app was popularized in responding to user queries 24/7. The users of the Varo Bank app will also get a virtual visa® debit card instantly that gives the users access to 55,000+ fee-free Allpoint® ATMs in stores like Target, CVS, and Walgreens.

This innovative mobile banking application also facilitates the users to send money across Varo and external bank accounts, get transaction alerts, and track spending on the go.

Recommend to Read: Power Of AI & ML Technologies In Banking & Finance

#6. USAA-The Best Android/iOS App for Banking, Finance, and Investment

The USAA Mobile banking app gives convenient and secure access to bank accounts from mobile devices. With its secure features and robust functionalities, it has secured a position in the list of the top 10 banking apps in USA. This app helps users manage banking, finances, investments, and insurance accounts in an encrypted manner.

Send money with Zelle (USA-based digital payments network), pay bills, make mobile cheque deposits, check loan eligibility, calculate EMI, and access e-wallets are a few of the best advantages of USAA-like popular banking apps in the USA. Currently, the app has a 4.8 out of 5 star rating and over 5 million downloads.

#7. Ally Mobile- Trending banking app in the USA for banking and investments

Ally is a leading banking and finance app available for Windows, iOS, and Android. The app was developed by Ally Financial Company, headquartered in Detroit, Michigan, USA. To provide 24/7 support to customers, the company launched Ally Mobile App in 2012.

The core features and functionalities of these trending banking applications are Ally eCheck Deposit, Check account balances and transaction history, instant money transfer, view/download account statements, Zelle® for paying US bank accounts, Ally Messenger for chatting, Ally Invest to invest in US stocks and ETFs with zero commission fees. This app also helps users to find the nearest ATMs by enabling mobile GPS.

How much does it cost to develop an on-demand android banking app like Ally Mobile Banking?

If you are looking ahead to banking app development and planning to launch it in the USA, here are the best features that must be added to a mobile banking application.

What Features Will Give Success To Your New Banking App?

The above list of mobile banking apps in the USA is popularized with the features they offer their customers. Mobile app design, features, and functionalities decide the success rate of the application. The cost to create a mobile banking app also highly depends on the features you have added.  Being one of the best Banking and FinTech mobile apps development companies in the USA, we have compiled a list of the must-have features in banking apps to ensure their success in the app stores.

• Easy registration & login: Give flexibility to the users to access the app functionality using their mobile number or email address.
• Account/profile management to allow users to edit profiles as per their needs.
• Provide high security for the user’s confidential data.
• Real-time data analytics and reports to give a clear representation of account information in charts and help them in analyze their account performance
• Instant money remittance feature to send/receive money securely across internal and external banking accounts through secured payment gateways.
• Instant payments anywhere at anytime.
• Pay bills feature to pay credit bills.
• Push notifications & updates feature to send alerts to the users about transactions and investments.
• Give access to customer service by enabling the in-app chatbot feature.
• Flexibility to add multiple bank accounts
• Secure password and fingerprint authentication ways
• Transactional and promotional alerts
• Locating the nearest branches and ATMs
• Enable QR code payments for fast and secure mobile payments.
• Integrate a spending tracker for provide valuable insights into the accounts.
• Integrate your banking app with popular e-payment or mobile wallet payment apps like Google Pay and PayPal.

 

How Much Does It Cost To Build Mobile Banking Apps?

Estimating the cost to create a mobile banking app is quite difficult. Mostly, the cost of developing a banking app will be around $40,000 to $250,000. However, this estimated development cost will depend on app features, app platform, app type, app design, and User Interface (UI) complexity. Further, the hourly rate of mobile app developers in the USA will differ from the mobile app development companies located in India.

Besides, the estimated cost of the banking application development (android or iOS) will also depend on the mobile app development team size and the overall time taken by the mobile Application Development Company that you hire.

Would you like to know the actual Mobile Banking App Development Cost? Get in Touch to get a free quote on Banking App Cost Estimate!

Do you have any banking app development ideas?

Let’s talk to USM Business Systems– the best mobile banking apps development company in the USA.  We develop custom mobile applications for the banking and finance industry. We help you with estimated banking app development cost so that you can align them with your budget.

We use cutting-edge Artificial Intelligence (AI) and Machine Learning (ML) capabilities to create next-generation digital banking and financial solutions that increase customer retention rates, prevent fraudulent acts, and reduce overall operating costs for banks.

Get in touch to know more about USM’s mobile banking development services!

[contact-form-7]

How to Maximize Business Productivity with Top DevOps Automation Tools?

In the fast pace of today’s business world, it is no longer about the creative thinking but more on getting the software solutions done effectively, quickly, and in a reliable manner. This is when DevOps principles and automation enter into the game. DevOps ensures seamless communication and continual improvement by connecting development and operations teams.

However, it is not easy to manage the complex processes and ensure successful deployments. So, automation systems specifically designed for DevOps will simplify these processes and increase productivity. These systems allow companies to automate repetitive activities, reduce errors, and focus on innovation.

Now let’s see some of the most impactful DevOps automation technologies available today. By exploring this information, you can identify the ones that align best with your organization’s specific requirements.

What is DevOps Automation

DevOps automation is the use of tools and scripts to automate repetitive and time-consuming processes throughout the DevOps lifecycle. This includes code integration, testing, deployment, monitoring, and infrastructure management. Businesses that automate these processes can lower manual intervention, reduce errors, and fasten delivery pipelines.

At its core, DevOps aims to improve the collaboration between the operation and development teams. Automation will remove the bottlenecks, improve collaboration, and standardize procedures. Thus, resulting in smoother workflows and more predictable outcomes.

Benefits of DevOps Automation Tools

1. Quick Time-to-Market: Automation fastens development and deployment, which allows companies to provide updates and features quickly
2. Improved Reliability: Automating the processes provides consistency and decreases the chances of human error.
3. Improved Scalability: Companies can handle increasing workflows efficiently by automating infrastructure and other processes.
4. Cost-Effectiveness: Automation systems can lower the demand for manual labor and operational overhead by simplifying operations.

DevOps automation is important for businesses to transform complex and time-consuming processes into manageable workflows. So, teams can focus on innovation and strategy.

Key Areas of DevOps Where Automation Matters

Automation is the foundation of a successful DevOps strategy, supporting all phases of the software development lifecycle. Businesses that automate specific areas can improve collaboration and speed results. Here are the primary areas in which DevOps automation has the most impact:

1. Continuous Integration and Delivery (CI/CD)

In traditional processes, integrating code from different developers into a shared repository is difficult and error-prone. This procedure is automated using CI/CD tools, so the changes are merged, tested, and delivered easily. Hence, it reduces time spent on manual testing and deployment.

2. Infrastructure as Code (IaC)

Manual infrastructure management is time-consuming, especially for large applications. IaC enables developers to specify infrastructure configurations in code, making it easier to provision, manage, and replicate environments automatically. Hence. DevOps enhances consistency and avoids setup errors.

3. Monitoring and Incident Management

Real-time monitoring tools will track performance bottlenecks, irregularities, and system failure. So, automation in this case will ensure the earlier detection and rectification of problems. This will thereby reduce downtime, improve system dependability, and encourage proactive problem solving.

4. Quality Assurance and Testing

Manual testing is time-consuming and might miss key issues. So, the testing processes have to be automated, and then the updated codes can be tested extensively and efficiently before they hit the market. Therefore, DevOps enhances quality and testing efficiency.

Automating these critical processes will make businesses more productive as the development cycles are reduced, and the teams get more aligned. 

Top DevOps Automation Tools to Increase Productivity

Choosing the proper DevOps automation tools is critical to increasing productivity and maintaining smooth operations. The following are some of the most effective tools used by firms to streamline their DevOps processes.

1. Jenkins

Jenkins is an open-source continuous integration and delivery (CI/CD) automation tool. It assists developers in automating tedious processes such as the development, testing, and deployment of applications.

Jenkins’ 1,500 plugins are versatile for all sorts of development needs. It automates the development procedures and makes delivery speedier and more reliable by ensuring that firms meet rigid deadlines within quality controls.

2. Docker

Docker has transformed the way programs are produced and deployed through containerization. Since Docker containers are lightweight and portable, they ensure consistency across multiple settings, from development to production. By eliminating compatibility difficulties, it offers developers a streamlined platform for creating, sharing, and executing apps. Thus, Docker helps businesses improve efficiency and minimize operational overhead.

3. Kubernetes

Kubernetes is a very essential tool for enterprises that run large-scale or microservice-based applications. It deploys, scales, and manages applications in an automated way. Its features include load balancing, self-healing, and automatic resource allocation, making it ideal for enterprises that wish to scale their operations smoothly.

It also reduces the complexity of maintaining distributed systems, thus resulting in consistent performance even under severe workloads.

4. Ansible

When it comes to configuration management and infrastructure automation, Ansible is notable for its simplicity and efficacy. Ansible lets enterprises automate processes such as server provisioning, application deployment, and configuration management. It allows enterprises to decrease manual involvement, minimize errors, and assure consistency throughout their infrastructure.

5. Terraform

Terraform is another platform that focuses on automating infrastructure provisioning. It employs declarative configuration files to manage resources across several cloud providers, including AWS, Azure, and Google Cloud.

Terraform’s flexibility makes it an excellent choice for enterprises that operate in hybrid or multi-cloud environments. Terraform automates infrastructure deployment, saving time and ensuring consistent environments, both of which are essential for high productivity.

7. Selenium

Selenium is a popular choice for automated testing. With its browser-based testing, teams can use it to recreate user interactions and verify applications across several platforms. Selenium is flexible and adaptive to several development environments as it supports a large number of programming languages.

How to Choose the Right DevOps Automation Tool for Your Business?

Selecting the right DevOps automation tool is a critical step in enhancing your company’s productivity and efficiency. With a variety of tools available, evaluating them against your specific business needs and objectives is essential.

1. Determining Business Requirements

Identify which specific steps in your DevOps workflow need to be automated. For example, a CI/CD platform like Jenkins can be the best option if deployments are regularly delayed. Terraform and Ansible are two solutions that may efficiently automate time-consuming manual infrastructure management activities.

2. Flexibility & Scalability

The technology you choose should help your firm expand, manage growing workloads, and change with your demands as your business does. For instance, Kubernetes automates scalability and maintains optimal performance under high demand, making it an excellent choice for businesses anticipating significant expansion.

3. Integration Capability.

DevOps workflows may need collaboration of several tools, therefore your automation solutions must integrate easily with your existing systems and procedures. For example, Docker and Kubernetes work well together to provide a unified environment for containerized applications.

4. Cost

Conduct a cost-versus-return-on-investment analysis to assess whether the tool’s advantages outweigh the costs. Some technologies, like Jenkins and Prometheus, are open source and free to use, whilst others may demand license fees or investments in training and installation.

5. Learning curve

DevOps tools are simple to use and easier to implement even for teams with little expertise in automation.

Assessing these variables, you may select the best DevOps automation technologies for your business needs, allowing you to increase efficiency and productivity.

Best Practices for Using DevOps Automation Tools

To reap the most benefits from DevOps automation solutions, they must be used efficiently.

1. Begin Small and Grow Gradually

Companies should begin by automating a specific procedure or operation like CI/CD pipelines or infrastructure provisioning. Later, when the team gains confidence and the process stabilize, automation can be expanded to further areas.

2. Prioritize Team Collaboration

Include the development and operations teams in decision-making and implementation. Their collaboration ensures that the products fulfill both parties’ needs while also improving overall workflows.

3. Training and Development

Equipping your staff with the relevant knowledge and skills to adequately use the selected tools, with workshops, online courses, or certificates to help enhance their skills.

4. Monitor and Optimize

Set key performance indicators and track the performance of automated processes. Regular monitoring of these analytics helps you detect bottlenecks, streamline workflows, and confirm that the tools are providing the maximum value.

5. Security and Compliance

Automation tools should comply with your organization’s security rules and industry standards. Regular updates are important for mitigating potential dangers.

6. Pre-Built Templates and Modules

Tools like Terraform and Ansible include pre-built settings, making implementation simple and efficient. These tools accelerate the automation process.

7. Integrate Automation

To avoid confusing employees with several tools, integrate them gradually. This also allows time to adopt the changes and troubleshoot.

8. Update Tools and Processes Regularly

Automation should adapt according to your organization’s needs. Update tools with the latest versions to have access to new features and top performance.

The effective use of DevOps automation solutions by businesses that follow these best practices leads to efficiency, cooperation, and productivity.

Conclusion

DevOps automation solutions have become important for businesses looking to increase efficiency and production. By automating tedious activities, boosting collaboration, and decreasing errors, these technologies allow teams to focus on creating high-quality software more quickly.

At USM Business Systems, our expertise lies in assisting businesses in identifying the best DevOps tools and methods to meet their specific needs. Whether you’re just getting started with DevOps or want to improve your current procedures, our team can help. Partner with us to update your operations, decrease complexity, and achieve long-term success through effective DevOps automation. Let us work together to create a stronger, more agile company future.

 

[contact-form-7]