All posts by USM

Artificial intelligence In The Workplace : Benefits & Examples

Best Examples of Artificial Intelligence in the Workplace

Artificial intelligence in workplace- It is very difficult to imagine the future of the workplace without Artificial Intelligence (AI) technologies. Artificial intelligence and robotics and their impact on the workplace management in the current and next few years would be high and cannot be imaginable. AI applications can automate the routine tasks of the firm so that the employees can focus on other creative works and improve their productivity.

We can say that AI allows employees to concentrate more on the impactful works of the organization. With the adoption of AI in workplace, the productivity, work quality, and business efficacy of an organization can be optimized. Such digital processes will help enterprises focus on accomplishing complex and mundane tasks in a very short time.

AI technologies are not only transforming our homes but also various industries. It can advance the accuracy, proficiency, and exactness of the firm tasks. But, many people have a lot of doubts regarding Artificial Intelligence and its impact on the workplace.

Numerous people think that the growth of AI will replace the human workforce. Machines and robots are becoming threats to the human workforce though they are beneficial for society. But, Artificial Intelligence  in workplace helps the enterprise to do tasks in a smarter and better way.

Now, let’s look at the best examples of AI in the workplace and we will also have a brief discussion on how AI is transforming the workplace of an organization.

Examples Of Artificial Intelligence In The Workplace

AI In Workplace For Executing Administrative Jobs

Nowadays, artificial intelligence apps for workplace are gaining momentum across digital niches. The use of artificial intelligence and robotics and their impact on the workplace for automating repetitive administrative tasks. Hence, AI applications will help admin in digitally maintaining the company’s information and assist employees in concentrating more on creative, revenue-generating, & productive tasks.

To include wonders to your business, take the help of USM’s AI-powered apps!

[contact-form-7]

AI Builds Interactive Platform Amid Employees And The Company

It is one of the key benefits of Artificial Intelligence in workplace management. In the workplace, the most important task is managing human resources. Better management of the workforce will assist companies in improving employee retention and achieving business objectives smoothly.

AI-powered applications and systems will help the organization in optimizing the employee experiences and increase retention. Collaborative AI-based HRMS (Human Resources Management Solution) will create an interactive platform that aids both company and employees to connect virtually and improve experiences.

AI In Workplace For Automating Hiring Process  

It is one of the top benefits of artificial intelligence in workplace. AI software applications, using ML and deep learning technologies automate candidate selection, screening, and recruitment process. AI apps for Android and iPhone can analyze the candidate qualification, verify the experience of the applicants, and find out the right candidate for the right position.

AI In Workplace Improves Productivity

Each & every organization needs a collection of data sets. By utilizing Machine Learning algorithms, the collected data can be analyzed and processed efficiently and accurately. Businesses can derive results-driven insights into operational and functional data and build strategies for improving productivity. AI applications generate valuable predictions in the data and enhance productivity.

Improving Customer Service

It is one of the best examples of AI in the workplace management. AI-powered Chatbot applications help organizations stay available 24*7 and better support their customers at all times.

Intelligent and interactive AI Chatbots or virtual assistants can understand user commands and gives accurate responses instantly. AI applications can deliver better services than a human workforce. With the help of these Chatbots, organizations can give quick responses to customer problems in less time.

AI Business Apps Increases Sales

AI in workplace improves sales and marketing functions. The best AI software solutions for businesses can perform and manage tedious tasks such as identifying potential leads and converting leads into customers. The sales representatives can track and continuously monitor the lead pipeline from anywhere at any time using AI tools.

CRM (customer relationship management) tools are the best examples of artificial intelligence in the workplace. AI-based CRM application allows sales people to digitally store customer contact details, identify sales opportunities, better manage orders and view delivery status, and intelligently perform brand promotional campaigns, etc.

CRM-like AI apps can help the organization bring entire sales operations onto a single digital platform and increase visibility into sales and marketing operations, and enrich brand-to-customer interactions.

Facilitating Collaboration

It is one of the best use cases of AI in the workplace management. AI systems and tools will play a key role in automatic scheduling and sending meeting invitations to employees based on the input given to the software solutions.

On the other hand, AI applications for workplace management allow project managers to collaborate with teams working in various locations and ensure quality output.

Supporting Innovation

It is one of the notable examples of AI in the workplace or business management. In the workplace, AI technology helps to create favorable circumstances to innovate new products and services. As AI tools have taken over mundane tasks, employees get much free time to interact with the customers and get their valuable feedback.

These are a few examples of artificial intelligence in the workplace management. Artificial intelligence and robotics and their impact on the workplace will be high and cannot be imaginable.

Benefits Of Artificial Intelligence in Workplace

From the above-discussed points, we can realize that AI technology will replace repetitive or complex problem-solving tasks very soon. In industries, in the place of human beings, AI-enabled systems will take decisions. Customer support & financial decisions are done using AI.
A large number of tasks get affected by AI, so it is very much important to evaluate the drawbacks of AI technology.

• To take advantage of AI technology, it is necessary to utilize its capabilities in the right direction.
• Governments must guarantee that everyone can get the advantages of AI to stop social inequality.
• To save the extra cost of implementing AI-powered systems in workplaces, employers should give training to the employees to upgrade their skills.

We have to utilize the power of AI in a proper way to get benefits. Artificial Intelligence will transform the workplace. Rather than concentrating on negative points of advanced technologies, businesses should grasp the profits from the new technologies.

Approach USM, the leading AI service provider & get success with our AI Solutions and Services!

Get in Touch!

[contact-form-7]

 

Artificial intelligence In The Workplace : Benefits & Examples

Best Examples of Artificial Intelligence in the Workplace

Artificial intelligence in workplace- It is very difficult to imagine the future of the workplace without Artificial Intelligence (AI) technologies. Artificial intelligence and robotics and their impact on the workplace management in the current and next few years would be high and cannot be imaginable. AI applications can automate the routine tasks of the firm so that the employees can focus on other creative works and improve their productivity.

We can say that AI allows employees to concentrate more on the impactful works of the organization. With the adoption of AI in workplace, the productivity, work quality, and business efficacy of an organization can be optimized. Such digital processes will help enterprises focus on accomplishing complex and mundane tasks in a very short time.

AI technologies are not only transforming our homes but also various industries. It can advance the accuracy, proficiency, and exactness of the firm tasks. But, many people have a lot of doubts regarding Artificial Intelligence and its impact on the workplace.

Numerous people think that the growth of AI will replace the human workforce. Machines and robots are becoming threats to the human workforce though they are beneficial for society. But, Artificial Intelligence  in workplace helps the enterprise to do tasks in a smarter and better way.

Now, let’s look at the best examples of AI in the workplace and we will also have a brief discussion on how AI is transforming the workplace of an organization.

Examples Of Artificial Intelligence In The Workplace

AI In Workplace For Executing Administrative Jobs

Nowadays, artificial intelligence apps for workplace are gaining momentum across digital niches. The use of artificial intelligence and robotics and their impact on the workplace for automating repetitive administrative tasks. Hence, AI applications will help admin in digitally maintaining the company’s information and assist employees in concentrating more on creative, revenue-generating, & productive tasks.

To include wonders to your business, take the help of USM’s AI-powered apps!

[contact-form-7]

AI Builds Interactive Platform Amid Employees And The Company

It is one of the key benefits of Artificial Intelligence in workplace management. In the workplace, the most important task is managing human resources. Better management of the workforce will assist companies in improving employee retention and achieving business objectives smoothly.

AI-powered applications and systems will help the organization in optimizing the employee experiences and increase retention. Collaborative AI-based HRMS (Human Resources Management Solution) will create an interactive platform that aids both company and employees to connect virtually and improve experiences.

AI In Workplace For Automating Hiring Process  

It is one of the top benefits of artificial intelligence in workplace. AI software applications, using ML and deep learning technologies automate candidate selection, screening, and recruitment process. AI apps for Android and iPhone can analyze the candidate qualification, verify the experience of the applicants, and find out the right candidate for the right position.

AI In Workplace Improves Productivity

Each & every organization needs a collection of data sets. By utilizing Machine Learning algorithms, the collected data can be analyzed and processed efficiently and accurately. Businesses can derive results-driven insights into operational and functional data and build strategies for improving productivity. AI applications generate valuable predictions in the data and enhance productivity.

Improving Customer Service

It is one of the best examples of AI in the workplace management. AI-powered Chatbot applications help organizations stay available 24*7 and better support their customers at all times.

Intelligent and interactive AI Chatbots or virtual assistants can understand user commands and gives accurate responses instantly. AI applications can deliver better services than a human workforce. With the help of these Chatbots, organizations can give quick responses to customer problems in less time.

AI Business Apps Increases Sales

AI in workplace improves sales and marketing functions. The best AI software solutions for businesses can perform and manage tedious tasks such as identifying potential leads and converting leads into customers. The sales representatives can track and continuously monitor the lead pipeline from anywhere at any time using AI tools.

CRM (customer relationship management) tools are the best examples of artificial intelligence in the workplace. AI-based CRM application allows sales people to digitally store customer contact details, identify sales opportunities, better manage orders and view delivery status, and intelligently perform brand promotional campaigns, etc.

CRM-like AI apps can help the organization bring entire sales operations onto a single digital platform and increase visibility into sales and marketing operations, and enrich brand-to-customer interactions.

Facilitating Collaboration

It is one of the best use cases of AI in the workplace management. AI systems and tools will play a key role in automatic scheduling and sending meeting invitations to employees based on the input given to the software solutions.

On the other hand, AI applications for workplace management allow project managers to collaborate with teams working in various locations and ensure quality output.

Supporting Innovation

It is one of the notable examples of AI in the workplace or business management. In the workplace, AI technology helps to create favorable circumstances to innovate new products and services. As AI tools have taken over mundane tasks, employees get much free time to interact with the customers and get their valuable feedback.

These are a few examples of artificial intelligence in the workplace management. Artificial intelligence and robotics and their impact on the workplace will be high and cannot be imaginable.

Benefits Of Artificial Intelligence in Workplace

From the above-discussed points, we can realize that AI technology will replace repetitive or complex problem-solving tasks very soon. In industries, in the place of human beings, AI-enabled systems will take decisions. Customer support & financial decisions are done using AI.
A large number of tasks get affected by AI, so it is very much important to evaluate the drawbacks of AI technology.

• To take advantage of AI technology, it is necessary to utilize its capabilities in the right direction.
• Governments must guarantee that everyone can get the advantages of AI to stop social inequality.
• To save the extra cost of implementing AI-powered systems in workplaces, employers should give training to the employees to upgrade their skills.

We have to utilize the power of AI in a proper way to get benefits. Artificial Intelligence will transform the workplace. Rather than concentrating on negative points of advanced technologies, businesses should grasp the profits from the new technologies.

Approach USM, the leading AI service provider & get success with our AI Solutions and Services!

Get in Touch!

[contact-form-7]

 

How is 5G Technology Impacting Mobile App Development?

As the reach of 5G technology starts to expand globally, businesses in all sectors realize the evolutionary benefits and implications thereof. For mobile app developers, 5G means more than just speed. It represents a completely new level for app planning and building and experiencing.

With this technology, apps will be able to deliver smoother experiences with responsiveness to end-users, especially for real-time communication applications, games, and mobile applications relying on the Internet of Things.

In this article, we will take a view of how 5G has implications on mobile app development and why it is essential to remain ahead of the curve for success. 

What is 5G Technology?

5G is the fifth-generation technology related to the mobile network, planned to offer faster data throughput, lower latency, and improved connectivity. It is faster than 4G and ensures download rates at a speed up to 100 times than other previous generations. Its capacity to send data in real-time with low delay, handle more connected devices, and deliver more bandwidth transforms mobile apps. These characteristics are particularly crucial for app developers working with technologies such as augmented reality (AR), virtual reality (VR), and the Internet of Things. 

How Does 5G Technology Impact Mobile App Development? 

1. Faster Speed

The ultimate standout of 5G technology is its unmatched speed-a clear advancement compared with the already outstanding 4G. With the potential for data transfer speeds at as high as 10 Gbps, mobile applications will be able to perform operations and distribute material much better. Apps will load faster, seamlessly update, and give a much more fluid user experience and this will be so even for data-intensive applications.

For mobile gaming, streaming platforms, and multimedia-rich apps, 5G’s speed transforms how users interact with content. Games with high-definition graphics or complex multiplayer environments can run without lag, and video streaming apps can deliver ultra-high-definition (UHD) videos with virtually no buffering. This also enhances interactive aspects to assure more fluid engagement with comments in social media, live streaming, and gaming apps.

As compared to earlier networks, 5G offers more speed. Due to this, mobile application developers can provide more innovative and dynamic experiences.

2.  Minimal Latency

Ultra-low latency is one of the greatest innovations in 5G technology. Compared to 4G networks, 5G networks could even provide a latency as low as 1 millisecond whereas, on most 4G networks, the latency is found to take from 30 up to 50 milliseconds.

Augmented and virtual reality applications require low latency. For example, for smooth and interesting streaming, AR applications need data to be sent in quickness. Similarly, low latency ensures there will not be any kind of lag or motion sickness in VR applications hence it becomes helpful in entertainment as well as educational sectors.

With 5G’s low latency, these apps can deliver high-quality video and voice calls with minimal delay, making remote meetings and consultations more fluid and reliable.

For businesses, the ultra-low latency of 5G opens up new possibilities for developing apps that offer seamless real-time experiences, whether it’s live collaboration, gaming, or AR/VR applications.

3. Expansion of IoT-Connected Mobile Apps

5G supports a large number of devices at once, which makes it perfect for the Internet of Things (IoT). While 4G struggles with multiple connections, 5G can handle them smoothly. This means IoT apps will run better, with fewer delays or interruptions.

Mobile apps can now easily connect with smart devices like home appliances, wearables, and industrial tools. For example, smart home apps can control things like lights and security in real time. Wearable devices, such as fitness trackers, can give instant updates on health data because of 5G’s fast processing.

4.  Improves cloud-based mobile applications

Cloud-based mobile applications benefit the most from 5G technology. Its speed and low delay let the apps run smoothly while relying on the cloud for data storage and processing. With 5G, apps can access data from the cloud faster, leading to better performance and less waiting time for the users.

This is especially crucial for businesses that use apps for data-heavy tasks. For example, companies that use real-time collaboration tools or apps that need large amounts of data, like video editing or graphic design platforms, will see improvements. It allows users to upload, download, and access files much quicker, even when working with high-quality content.

Additionally, 5G supports edge computing, where data is processed closer to the source instead of in a distant cloud server. This reduces the time it takes for apps to respond, making them more efficient. For industries like healthcare or logistics, where quick access to data is critical, this improvement can be a big advantage.

5.  Security and Privacy of Mobile Apps

Security has become a major issue as 5G connects more devices. As more data moves between apps and networks, hackers now have more opportunities as a result. To secure apps developed for 5G, developers must take additional precautions. The main challenge is the increased data traffic. With 5G’s fast speeds, hackers can quickly steal large amounts of data if security measures are weak. Encryption becomes more important to protect sensitive information. Developers should also focus on securing communication between multiple devices, especially in IoT apps.

The increased quantity of attack points is further cause for concern. Since 5G links more devices, every one of them becomes a possible target. The network’s developers are responsible for ensuring the security of each device. This means implementing strong authentication procedures and routinely upgrading the guidelines.

App developers can create more secure and safe apps for the 5G era by keeping these issues in mind. Security needs to be the main concern as more businesses and consumers use 5G-enabled apps.

 

The Future of 5G in Mobile Application Development

Although 5G is still in its early stages, it has enormous potential. As more organizations and industries adopt 5G, mobile apps are expected to evolve. Developers can design complex apps that run faster, interact in real-time, and perform more efficiently. This opens up new opportunities for apps in sectors such as healthcare, gaming, and education.

We will also see an increase in AI-powered applications requiring real-time data processing. Because of 5G’s low latency, apps may provide instant feedback and predictive analytics, allowing businesses to make more informed decisions. AR and VR apps will prosper, offering more immersive experiences.

Businesses should remain ahead of the curve by implementing 5G technology now. Those who adopt it early on can develop apps that provide better services and get a competitive advantage in the market.

As 5G becomes the mainstream, it will change what people expect from mobile apps, requiring developers to create quicker, smarter, and more imaginative solutions.

Conclusion

5G is more than just a high-speed network, as it represents a fundamental transformation in how mobile apps are created and utilized. With its fast speeds, low latency, and capacity to connect more devices, 5G is creating new opportunities for mobile app developers and enterprises. 5G is transforming the future of mobile technology by enhancing real-time experiences and performances of cloud-based and IoT apps. Businesses using 5G can develop innovative apps, improve user experiences, and remain ahead of the competition.

As 5G expands globally, its impact on mobile app development will only rise, opening up new avenues for innovation and growth. To truly benefit from everything 5G technology has to offer, developers and businesses must embrace it and reconsider their app strategy.

 

[contact-form-7]

AI vs Automation: Understanding the Key Differences and Their Impact

In our high-speed era of a fast and furious digital lifestyle, the terms “automation” and “Artificial Intelligence (AI)” are drivers. While at first glance they appear to speak of the same things robots doing things with little human intervention, they are actually distinct technologies and have different jobs and impacts.

Knowing the main differences between automation and AI is vital, particularly with businesses and society becoming more reliant on them. This article discusses the difference between automation and artificial intelligence, challenges, and applications on industries and employees.

What is Automation? 

Automation means applying technology to perform tasks with little or no human intervention. The overall goal of automation is to create efficiency, consistency, and speed. Through automation, we can definite procedures, rules, or processes, which are performed by equipment without having to “think” or “learn.”

Types of Automation 

1. Fixed or Hard Automation: Applied in manufacturing, it is extremely structured, repetitive work with minimal variation.
2. Programmable Automation: Applied to batch production, the machines are reprogrammed to perform many different tasks.
3. Flexible or Soft Automation: Provides more flexibility, usually in robots or machines switched from task to task with little setup.
4. Business Process Automation (BPA): Used in the cyber world to perform repetitive tasks such as data entry, scheduling, and system monitoring.  

What is Artificial Intelligence?

Artificial intelligence, however, is the simulation of human intelligence on machines. AI allows systems to learn through experience, adapt, and make decisions based on sophisticated algorithms instead of pre-programmed rules.

Core Capabilities of AI 

1. Machine Learning (ML): Allows systems to learn over time from experience.
2. Natural Language Processing (NLP): Allows machines to read and write natural languages.
3. Computer Vision: Allows machines to read and react to visual input.
4. RPA (Robotic Process Automation): Allows rule-based autonomous operations and choice in the physical world.

While automation only gets to do things according to the rule, AI gets to handle uncertainty, solve issues, and even mimic such high-level thinking as learning and solving problems.

Real-World Applications of AI and Automation 

Automation in Practice 

• Manufacturing: Robot arms, automated conveyor belts, and quality checks.
• Finance: Automated fraud detection and transaction processing.
• Retail: Automatic restocking and checkout software.
• IT Operations: Server monitoring, backup infrastructure, and software deployment. 

AI in Practice 

• Healthcare: Predictive patient care insights, AI-based diagnostic tools.
• Finance: Customer sentiment analysis, credit risk models, algorithmic trading.
• Marketing: Recommendations, advertisement targeting, customer segmentation.
• Transportation: Autonomous cars and AI-based logistical planning. 

Automation Vs AI: Impact on Industries

Manufacturing 

• Automation Impact: Increased productivity and reduced labor costs because of optimized production lines.
• AI Impact: Predictive maintenance, computer vision-based quality control, and optimized supply chains. 

Healthcare 

• Automation Impact: Automated scheduling of appointments, billing, and automatic updating of patient records.
• AI Impact: Diagnostic imaging, virtual health assistants, personalized treatment plans. 

Retail

• Automation Impact: Inventory, checkout.
• AI Impact: Dynamic pricing, customer behavior analysis, virtual shopping assistants.

Challenges of AI and Automation Adoption 

1. Fear Of Employment Replacement

With automation and AI doing the repetitive jobs, many of the jobs, especially those in sectors like manufacturing and retail, are disappearing. This is supporting more stress on low-skilled workers and can widen the gap between the poor and rich.

2. Surveillance and Data Privacy

AI needs large amounts of data to operate optimally, but getting all that data is a direct threat to privacy. Tools like facial recognition can track people without their permission, overstepping on basic rights and freedoms if unregulated.

3. Transparency and Accountability

AI decides on black processes, but even to those who create it. However, when something goes wrong, like an incorrect medical diagnosis, it is unclear who is responsible.

4. Security and Safety Risks

As deals with data, AI systems can be hacked with disastrous effects. For instance, autonomous vehicles might be tricked by bogus information, or AI might be employed in cyberattacks. Strong defenses must be constructed to make these systems safe and secure.

5. Overdependence and Loss of Skills

As we increasingly depend on AI to make routine decisions, there’s a chance we’ll begin losing our own capabilities. If we let the machines do all the thinking for us, we’ll be forgetting how to make decisions, solve problems, or even perform our work efficiently without them.

The Future: Synergy, Not Substitution 

True potential is not either-or, automation vs. AI, but mastering how to use them together. Used correctly:

• Automation can handle repetitive, routine work.
• AI can bring in intelligence and responsiveness.
• Human beings can focus on strategy, creativity, and empathy work.

These companies that capitalize on this synergy will be able to innovate, compete, and build strong futures. 

The Cost of AI Development 

The expense of building AI can be prohibitive, here are some reasons why it is so costly:

1. Research and Development

It is expensive to recruit skilled AI researchers, data scientists, and engineers. They are in-demand individuals and get compensated well. The finest AI talent usually comes from academia or leading tech companies, so it is competitive and usually pricey to recruit them.

2. Data Collection and Labeling

AI models need huge amounts of high-quality data to learn from, especially for healthcare applications, where data must be carefully curated and anonymized. Collecting, cleaning, and labeling such data is labor-intensive, which reduces costs.

3. Computational Resources

 

Training advanced AI models like large language models or computer vision requires enormous computational resources. That entails high-end GPUs or TPUs, which are extremely costly to buy or rent from cloud providers. The power consumption also commands a significant portion of ongoing operational costs.

4. Infrastructure and Maintenance

Building and maintaining AI infrastructure, including servers, storage, networking, and monitoring software, requires long-term investment.

5. Testing and Safety Measures

AI development involves a lot of testing, including model verification, bias identification, and safety checks. For self-driving cars or medical diagnostics, this testing must be highly specific, sometimes to the extent of requiring real-world tests and regulatory approval, and both are expensive.

6. Legal and Compliance Costs

AI development must meet regulatory requirements and adherence to law in data protection (e.g., GDPR) saves costs significantly.

7. Deployment and Scaling

Migrating an AI model means adaptation and interfacing with other systems. Scaling AI to numerous regions, languages, or platforms adds additional expense.

Also Read: How Much Does Artificial Intelligence Cost?

Conclusion

AI and automation are change drivers with inherent strengths and potential. Where automation works by speed through inflexible, fixed principles, AI is gifted with learning, growth, and decision abilities. Rather than setting the two against each other as new technologies, they are better placed to be put side by side as complementary technologies. They revolutionize the way of living, working, and existing with the world entirely together.

Connect with USM Business Systems, the best AI development company, to bring your dreams into reality.

 

[contact-form-7]

Artificial Intelligence In Business Application
5 Examples Of AI In Business Intelligence Applications

In the current scenario for ai in business application, data became crucial for every industry around the globe, and you know that 90% of the available information is generated in seconds leveraging intelligence Artificial Intelligence tools and it is impossible to gather such massive data from the human workforce.

AI based business intelligence applications are now a trend across the world. Organizations across various industries are implementing numerous applications of AI in business management and renovating their operational and functional flows to achieve their objectives in this digital space.

AI’s most significant technology Machine Learning (ML) is also disrupting the business intelligence mobile app development industry. To evaluate performance and match the progress with the targets, identify customer needs, predict customer preferences, and so on, organizations are increasingly investing in AI and ML-based business intelligence software applications and measuring their performance progress with ease.

Hence, the use of AI in business intelligence applications development is increasing since over the past few years. Today, in this article, we would like to walk you through:

• Practical examples of Artificial Intelligence in business intelligence applications that keep organizations competitive
• Applications Of AI In Business Management
• Reasons Behind Why Businesses Need AI-Powered BI Systems

Herein, we have discussed a few major business intelligence application development vendors like SAP, Siemens, GE, and other leading BI app developers that are designing and developing AI based business intelligence applications for businesses across various industries.

Practical Examples Of AI In Business Intelligence Applications

Here are the top use cases of AI-based business intelligence applications –

1. SAP’s HANA Platform

SAP is a Germany-based leading custom software development company. SAP platform consists of different models in their gallery, but as per our requirement, we are going to discuss SAP’s cloud platform HANA.

Most organizations use this software to manage databases of information they have gathered. To be more clear or precise, it will duplicate & ingests structured data like customer satisfaction from an app, relational databases, and many other sources.

You can install this HANA platform in different ways; one is by running on-premise via a company server or using a cloud source. The platform will collect information with the help of access points like financial transactions, equipment at production plants, desktop computers & mobile, and sensors across various business verticals.

If your salesperson is using a tablet or Smartphone to document purchase orders, and the data will be collected from those recorded transactions, which can be examined and analyzed by HANA platform to know customer or user problems and choices.

Walmart is one of the top retail chain stores (11,000) in the world and the USA, which doesn’t require any introduction. It is using the HANA platform to record & process its high-volume transactions that happen in 10 seconds.

2. Avanade’s Deep Analytics Platform

Avanade is the USA’s top IT consulting and services company that is engaged in providing artificial intelligence, business analytics, digital transformation, cloud migration, application development services, workplace management, and other enterprise-centric digital services and solutions.

Avanade is a company that is developed by two IT giants Accenture & Microsoft that has the capability to utilize Cortana intelligence and remaining solutions for data-based insights & predictive analytics.

Pacific Specialty, an insurance company that knocked on the doors of Avanade to develop a deep analytics platform with the focus to provide more information to its staff regarding the business. The insurance firm’s primary aim is to use policy & customer data to enhance team and company growth.

When you can understand your policyholders’ interests, trends, and behavior with the help of analytics, the company can give good advice about existing and new products that are available to the company.

Once, the company concluded that the coming future would be filled up with smart technologies where machines will do the maximum work that can be done by human resources. According to the study conducted by Avanade states that organizations can raise their revenue by 33% with the usage of smart technologies.

And they also revealed that it is going to create new job roles for professionals and many more benefits to users. It is also not precisely mentioned which professionals are going to be changed with the adoption of advanced smart technologies.

3. Apptus’ AI-powered eSales Platform

It is one of the best business applications for artificial intelligence. Apptus is a AI applications development company that is using AI for automation, streamlining operations, and enhancing the efficiency of processes.

Apptus has developed an AI-powered business intelligence platform- eSales for e-commerce and retail companies. This revolutionary application makes use of ML, NLP, predictive analytics, and deep learning like AI technologies and assists companies in automatically processing customers’ data and maximizing sales.

Apptus’ eSales platform identifies and analyzes data related to customers’ search and purchasing behavior and helps e-commerce service providers to display or send personalized product recommendations automatically. It will increase customer loyalty and optimizes sales value.

E-commerce companies are exploring 100% sales benefits using this platform. Based on search patterns, this AI & ML powered BI solution automates demand predictive tasks and creates conversions with ease.

Still, the technology is in the adoption stage, Cloudera Founder & CTO, said that deep learning is very good at anomaly detection and prediction. He also said it is getting simple for deep learning networks to comprehend what information is exactly authentic. And he also says, you cannot teach the platform what to work on, just provide a chunk of data from which it will sort out what it requires.

4. Siemens’ AI-based Reporting and Analytic Platform

 Siemens is using its ML technology to monitor and validate how its industry machinery equipment is working. The company launched MindSphere, an open industry cloud platform in beta.

The primary focus of this cloud platform is to monitor machine performance and detect defects for service requirements with the help of machine tools & drive train analytics.

This AI-powered BI application is being used by many industries to keep an eye on machinery and measure key performance metrics. Such prediction into devices will help companies make informed decisions about anticipatory maintenance & also be used to manage their equipment efficiently so that they can have a long lifespan.

When you compare Predix with MindSphere, the Siemens platform can work efficiently on every machine and plant regardless of the manufacturing industry. The core intention of the platform is to help plant operators to increase the uptime of their equipment and makes maintenance more competent by predicting when there is a possibility of machinery breakdown.

By using these types of platforms, industrial plants are seeing a reduction in maintenance costs. Siemens will provide a box whenever you opt for MindSphere, which you can attach to the machines, and it will collect the information related to the performance of the equipment by which the engineer can take action.

5. GE (General Electronics)

The latest technologies are taking a major part in the newest advancement in various industries. The usage of sensors increasing in physical equipment like vehicles, equipment spaces, machinery, and production plants, and these can be automated & analyzed by artificial intelligence.

When it comes to IoT, it is not about just consumer gadgets, oil rigs, commercial trucks, cargo ships, and trains can be automated or digitalized, examined, and predicted through networks.

Industries like aviation and oil & gas are using GE’s Predix operating system to know the historical performance data of the equipment by using the advantage of the industrial apps, which can be used to identify different types of operational outcomes like when there is a possibility of machinery failure.

If you think GE’s operating system is only for automating primary operations, then you have mistaken because it can process a large amount of information and prepare a forecast report within seconds.

The oil & Gas industry is using Accenture’s intelligent pipeline solution to examine pipelines that are a million miles across the globe. It gathers information from the pipelines & external sources for the safety and proper use of the resources.

When it comes to the airline industry, they are using an app called Aircraft Landing Gear that is built on Predix. The app helps airline engineering crews to check for how many days it will be in service before a flight is placed into the service. The app will prepare a schedule depending on the information that helps to minimize unexpected or unplanned equipment issues & flight delays.

For instance, this AI-based BI solution maximizes the performance of the equipment. After Pitney developed an automated solution on top of Predix, it raised its machinery yield by 20%.

These are a few examples of AI-enabled business intelligence applications. The above-listed BI applications developers are making use of revolutionary AI and ML technologies and tools and creating top-notch BI solutions for companies across all sizes.

Hire An AI App Development Company!

[contact-form-7]

Now, let’s take a look at the best use cases of AI in Business applications.

Applications Of AI In Business Management

The integration of AI, ML, predictive analytics, and deep learning technologies into BI applications will help organizations identify and predict market trends, customer behavior, and optimize overall performance progress.

Custom AI app development companies are assisting enterprises in building futuristic AI based business intelligence applications and playing a major in digitizing data collection, processing, and analyzing operations.

Let’s move on to how can AI empowers Business Intelligence Applications or ai application in business or artificial intelligence in business management.

• Integration of Artificial Intelligence in business application optimizes features and functionalities of BI
• AI and ML in BI applications make data storing and processing faster and help organizations derive valuable insights into customers’ data
• AI development companies are adding intelligent tech capabilities to BI applications to define and intelligently process raw information
• Artificial intelligence in business intelligence, along with ML, and deep learning algorithms, smoothly segregates input data and simplifies complex data analysis processes
• A blend of AI and Natural Language Processing (NLP) makes BI software solutions better understand voice commands and perform data analysis tasks accurately as defined or required by the organization

These are a few benefits of AI Business Intelligence applications. Operational efficiency, productivity, analytics and insights, quick decision-making, business scalability, virtualization and visualization, and cost savings are all key advantages of using AI in business intelligence applications development.

Hire top AI applications development companies and get your BI solution developed with a sort of enterprise-friendly features and functionalities.

Reasons Behind Why Businesses Need AI-Powered BI Systems

The explosion of new big data sources, such as mobile, tablets, and the Internet of Things (IoT) devices will no longer undermine businesses.

They need increasingly practical experiences. This prompts AI-driven BI frameworks that will dramatically change business data into simple, precise, real-time narratives and reports.

BI Apps Delivers Data Insights– AI in business applications for deriving insights is gaining popularity. Big data growth in the market makes it difficult to make strategic decisions within the deadline. In recent years, Artificial Intelligence has increased BI systems to provide dashboards that provide alerts and business insights to key decision-makers.

AI in Business Applications Fills Resource Gaps – There is a shortage of experts with data analytical skills worldwide, and the well-developed country, USA also has a shortage of 1.5 million (approx.) data analysts. Therefore, it is very important to hire data experts in each department of a company to complete the given tasks.

Preventing Data Overload – Data is growing at an unimaginable rate these days and can easily choke off the business activities of organizations. This is where AI-powered BI tools come in, when a company has data bursting its BI platform from different sources.

It aids to analyze all the information and provides customized insights. Therefore, investing in AI-based BI software can help organizations break down data into maintainable insights

 

Final Words

We conclude that the need for Artificial intelligence in business application development is high. AI-enabled BI applications development will have a bright scope in the years ahead.

It is the right time for businesses across industries to invest in AI business intelligence software. Companies can reduce resource overheads, better manage enterprise data operations, build sales strategies, well-handle leads, and get 100% returns on investment using BI solutions.

USM is the best AI development company in the USA and India. Our seasoned AI-based BI applications developers create outstanding app development strategies and develop full-fledged automation solutions that scale up your operations.

Are you looking to integrate AI solutions to get a high ROI?

Let us connect, Our AI expert team will guide you on the right path.

[contact-form-7]

How to Integrate ChatGPT into Your Business by Industry?

The integration of ChatGPT in business applications has brought in extraordinary advantages besides just improving the basic business functionalities, giving better customer experiences, and driving efficiencies over time. It could be applied to all other fields of organizations where there exist a need and potentialities by using the power of Artificial Intelligence (AI) and Generative AI (Gen AI).

 

In this article, we expand on how to better incorporate ChatGPT into various sectors, supply examples of its function by industry, and explain the advantages so that you can get the most out of this tool.

1. Healthcare Industry

The following a few best strategies of ChatGPT integration in healthcare systems.

• Patient Support

ChatGPT can be a virtual assistant for both on your website and patient portal. It can be used to respond to specific user questions regarding symptoms, treatments, and medications. ChatGPT integration with EHR systems helps companies process data and provide personalized recommendations based on patient information.

• Quick Appointment scheduling

Artificial Intelligence (AI) based ChatGPT integration in healthcare assists in organizing appointments, confirmations, and reminders. Integrating LLM models with internal scheduling software makes communications between healthcare providers and patients seamless.

• Mental Health Help

The incorporation of ChatGPT into mental health applications offers users preliminary assistance and guidance. So, the integration of ChatGPT with healthcare apps facilitates the process of establishing a communication bridge between patients with appropriate professionals for additional healthcare support.

Key Benefits of Integrating ChatGPT with Healthcare Mobile Apps

• 24/7 Support: ChatGPT provides 24/7 support to the patient, thus improving the access of information and services in any time zone.
• Less paper work: It automates routine procedures like appointments and many frequently asked questions, thus free ups employees for more complex tasks.
• Patient Experience Improved: Gives immediate and personalized answers that enhance the experience and interaction level of a patient.

2. Retail

The retail sector is one of the most promising sectors that could benefit from ChatGPT integration in its internal software applications.

Top GPT integration strategies in retail.

• Customer support

ChatGPT integration on your e-commerce website or end-user applications helps you manage requests about product details, the status of an order, return policies, refund statuses, etc. ChatGPT can be connected with CRM for more personalized support.

• Personalized shopping experiences

Using ChatGPT, businesses can keep track of customer preferences, browsing history, and needs. It helps them provide personalized product recommendations and improve their experiences.

• Virtual Shopping Assistant

ChatGPT integration in AI shopping assistants can aid in assisting customers on your website, comparing products, and making purchases.

Benefits of integrating ChatGPT in Retail Systems

• Boost Sales: ChatGPT integration in retail helps retailers provide personalized recommendations and ensures effective handling of queries that would increase sales and conversions.
• Cost-effectiveness: Since there is a reduced need for large pools of customer service personnel, routine interactions are reduced with chatbots.
• Higher Customer Engagement: It offers a much more interactive and responsive shopping experience and boosts customer engagements.

3. Financial Services

The following are the top three ChatGPT Integration Strategies for the Finance Sector.

• Customer Support

ChatGPT can automate time-consuming repetitive admin tasks, such as customer communications and transaction monitoring and management. With its integration into banking systems, financial organizations can boost their employee productivity.

• Fraud Detection and Security

Through the integration of AI ChatGPT, companies can track irregular patterns in customers’ behavior and identify suspicious transactions.

• Financial Advisory

Introduce ChatGPT in financial advisory websites to provide simple financial advice and counseling to customers through the chat service, as per their queries and monetary goals.

Top Benefits of integrating LLM Models into Finance Software

• Process Efficiency: Automates daily customer communications and transactions so that employees’ time is utilized for complex work.
• High Security: It helps to detect fraudulent transactions and eventually brings about much better security.
• Superior Customer Service: It helps companies provide instant and accurate responses to financial questions. Thus, GPT is augmenting the customer satisfaction level.

4. Education

ChatGPT Incorporation Methods into Education Systems

• Student Support

Incorporate ChatGPT into educational applications to provide prompt responses to students about their inquiries about courses, administrative procedures, and also research and tutorial support.

• Administrative Tasks

Use ChatGPT for streamlining routine administrative tasks, such as queries related to admissions and scheduling, to minimize the workload for the educational workers.

• Interactive Learning

Deploy ChatGPT in educational apps to improving students’ engagement, especially through quizzes and personalized feedback.

Benefits delivered to educational institutions with ChatGPT integration

• ChatGPT integration will help educational institutions provide instant access to the entire information and provide 24/7 support to the students, thus improving their learning experiences.
• It also streamlines administrative processes, helping staff to undertake some more strategic work and boost productivity.
• LLM Models supports the students even after class hours by offering them help without time constraints. It enhances their learning experiences and skills.

5. Travel and Hospitality

The following are the best ideas to integrate ChatGPT in travel apps.

• Booking Support

With the integration of ChatGPT with travel booking apps, it would speed up the process of booking flights, hotels, and rental cars. It would be able to also address all enquiries including questions on availability, prices, and change in details of the booking.

• Customer Service

Using ChatGPT, you can even answer questions that consumers have concerning their travel, changes in journeys, cancellations, even what to see locally.

• Local Recommendations

Use ChatGPT in travel apps to provide locals with personal suggestions on dining places, attractions, and activities that best fit the preferences of the users.

Top benefits of ChatGPT Integration into travel apps.

• Enhanced Customer Experience: By deploying ChatGPT in travel apps, businesses can provide seamless booking assistance and personalized recommendations to their users. Thus, it improves overall travel experiences.
• Operational Efficiency: By automating end-to-end procedures, AI ChatGPT reduces the need for manual intervention and improves operational efficiencies.
• Increased Revenue: Facilitates upselling and cross-selling of additional services and experiences, potentially boosting revenue.

6. Real Estate

ChatGPT Integration Strategies

•        Property Inquiries 

Usage of ChatGPT on your website helps customers inquire about their property listings, availability, and prices.

•        Lead generation

Apply ChatGPT when you engage with buyers and sellers to qualify them and schedule a viewing for the property. This will harmonize lead management with the systems in the CRM.

•        Market Insights

Use ChatGPT to let clients have an opportunity of market trends, properties, and any other type of investment-related possibility for their questions.

Benefits Of ChatGPT Integration in Real Estate Apps

 

• Lead Management Efficiency: Integration of ChatGPT in real estate mobile apps will help companies better manage the process of communicating with potential clients and qualifies leads in the conversion process.
• Better Discovery of Properties: Helps clients find properties that come within their scope of interest, therefore enhancing their experience.
• Cost-Saving: It reduces the need for detailed tracking and time-consuming follow-through that saves the operational costs.

 

Conclusion

ChatGPT would integrate into the business and would provide a transformative benefit across all sectors. Implementation of ChatGPT in areas to meet industry needs of healthcare, retail, finance services, education, travel, real estate, human resource, or automotive, maximizes experiences for customers and streamlining operations for greater efficiency. Strategic integration with continuous iteration and aligned to your business objectives will result in ChatGPT as a catalyst in further success towards your strategic objectives.

 

[contact-form-7]

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]