Tag: AI

We currently live in the eon of Artificial Intelligence. Whether we like to admit it or not, AI has suffused its way into every industry in all of its beautiful ingenuity.

Did You Know?

“The global artificial intelligence market size was valued at USD 93.5 billion in 2021.” – Grand View Research

“AI could contribute up to $15.7 trillion1 to the global economy in 2030.” – Sizing the Prize, PwC Report

What is Artificial Intelligence? 

Artificial intelligence (AI) is a simulation of human intelligence processed by electronic gadgets that enables the execution of an array of advanced functions, like seeing, understanding, and translating spoken and written language, data analysis, and many more.

From robots that can navigate a warehouse by themselves to virtual assistants that understand what people are saying and act upon that information, we can see Artificial Intelligence in play everywhere.

Read more: Reimagine Your Business with AI. Here’s How!

Artificial Intelligence-Based Code Generation Tools 

Let’s take a look at code-generation tools that are based on AI technologies. This article will discuss three such tools – Codex, Co-pilot, and ChatGPT.

1. Codex

As announced by the Artificial Intelligence Research Company OpenAI, the Codex model series is a successor of the GPT-3 series and is trained with both natural language and billions of lines of code. It is most competent in Python and is proficient in many more languages, including C#, JavaScript, Ruby, Swift, TypeScript, SQL, and even Shell.

Due to its understanding of many languages, Codex can transcribe simple commands in natural language and execute them according to the user’s preference. This makes building a natural language interface into existing applications possible. It also helps speed up the work of professional programmers and helps amateurs get started with coding.

2. Copilot 

GitHub Copilot, fabricated by GitHub and OpenAI, is a cloud-based AI tool that assists users of Visual Studio Code, Visual Studio, Neovim, and JetBrains integrated development environments (IDEs) with auto-completing code.

GitHub Copilot is trained on billions of lines of code and uses this knowledge to turn natural language prompts into deft coding suggestions. It is famous for evaluating and suggesting improvements for social media profiles, facilitating online presence across various digital channels.

Copilot uses AI technology to engage with potential leads through messages and categorizes them based on responses. It is trending with a whopping 4.67-star rating and is widely praised for its enormous support.

3. ChatGPT

OpenAI released yet another ingenious model called ChatGPT. It is a long-form question-answering AI that addresses complex questions conversationally. This is a revolutionary technology because it not only understands human language but is also trained to learn what humans mean when they ask a question.

The New York Times headlined, “ChatGPT and other chatbots is a ‘code red’ for Google search engine.”

While The Indian Express, in an article, stated that “When it was introduced, ChatGPT’s ability to break down complex problems and explain everything in a human-like manner led many to proclaim that Google’s days as the numero uno search engine are numbered.”

ChatGPT is undeniably a hot topic, and its reasons stand strong. Its dialogue format makes it possible to provide answers to any follow-up questions, accept its mistakes, challenge incorrect premises, and reject inappropriate requests.

Its specifically trained ability to understand the human intent behind every question and provide helpful, harmless answers while discarding parts of the question that do not make sense only adds to its special nature.

Read more: Is AI-powered Mobile App What  Your Business Needs Now?

Benefits Of These AI Tools

1. Codex –

“You just ask the computer to do something, and it just does it,” said OpenAI CTO Greg Brockman in the video demo of Codex.

Codex is good at co-referencing resolutions. It also links nouns in the prompt/input to their proper variables and functions in the code. Codex can also execute mundane tasks, like rendering web pages, launching web servers, and sending emails.

As AI technology takes over all the tedious parts, the programming process is prone to become more efficient. OpenAI shows Codex has a 37% accuracy rate in effectuating coding tasks.

2. Copilot –

A new study by GitHub revealed that Copilot works as an AI code programming assistant, significantly increasing developer productivity and happiness.

This particular AI-based code generation tool stands out because of its simplicity. You can describe the task you desire, outcome, or suggestion in the comments, and Copilot can come up with what it thinks are the proper lines of code. On the other hand, you can infer just your intentions with an incomplete prompt, and Co-pilot will do the code generation according to the same prompts.

3. ChatGPT –

Firstly, it reflects its efficiency by handling large volumes of conversation without needing breaks, which is undoubtedly helpful for customer service or other applications with a high demand for conversation. It also personalizes these conversations allowing them to feel unique for different users.

Using ChatGPT is highly cost-effective because it eradicates the need to hire human employees to handle conversation tasks. It is also available 24 hours a day throughout the week and has a great language support system.

How It Enables Reduced Costs 

Embracing Artificial Intelligence is a deft, cost-effective decision that most businesses and industries need to make. AI helps companies progress on many fronts, but the most imperative is its impact on the company’s pocket.

Implementing AI-based code generation tools such as Codex, Copilot, and ChatGPT reduces the need to hire miscellaneous employees to perform repetitive, tedious tasks. This, in turn, reduces the chances of any mishaps that may cost the company money to fix. Using these tools as assistants also greatly helps employees with their workload.

Using a more personalized, accurate, and compactable AI technology in your business can attract many potential clients and customers. This ultimately creates a profit for your business while also helping you establish your roots in the industry.

35% of consumers feel the desire to see more companies using chatbots. This is the perfect time to build the software you “ever needed” at a reduced cost.

Read more: Artificial Intelligence and Machine Learning for Faster and Accurate Project Cost Estimation

Myths Around The Use Of AI Tools 

The long-standing fear of technology taking over mankind has always had its chokehold on innovation. It is time to debunk the myths that surround AI and let technology progress.

Myth #1 – AI Is Going To Take Over Every Job Sector

One thing to remember is that no matter what, Artificial Intelligence tools will not replace the developers but increase developer productivity. It is reasonable to believe that AI has the potential to disrupt labor, but to compare labor from humans to machines directly is an unnecessary simplification. AI tools exist solely to enable humans to work in a newer and smarter way.

Myth #2 – AI Is Magic

The idea that AI tools can magically make sense of any and all of your messy data is completely erroneous. AI does not work on the principle of “load and go,” and the quality of input data is more important than the AI algorithm. This implies that the data being prompted has to be relevant to the problem being solved and specific to a set of use cases and a domain of knowledge.

What The Future Holds For The Industry With AI Tools

AI has consistently altered the course of the world multiple times and will continue to do so in the future. Although it is not a mainstream technology, billions of dollars are spent annually on AI research and development.

Did You Know?

As of the latest 2022 data, the global AI market is worth $136.6 billion. By 2030, the global AI market is expected to reach $1.81 trillion.

Some other industries that are largely affected by AI tools include –

• Software Development Companies
• Information Technology
• Finance
• Manufacturing
• Customer Service
• Education

Get Future-Ready With The Best of AI 

Using AI-based code generation tools can give you the upper hand you have been waiting for. Unlock your business’s potential with Fingent, the top custom software development company. Get in touch with our experts for a power boost and to get ahead of the competition.

From the moment we wake up, mobile apps have become an inseparable part of our lives! From sleep trackers to fitness apps to alarm clocks and everything in between, we rely on mobile apps to accomplish almost every daily task. Mobile apps also play a vital role in more complex choices in life, like dating. A world without smartphones and their apps cannot exist any longer. In such a scenario, businesses must continue to make smartphones smarter to stay relevant. The best way to achieve that is to empower mobile apps with Artificial Intelligence.

Are you wondering if your industry can benefit from AI-powered mobile apps? This blog will discuss that and explain how you can benefit from them. Let us begin by understanding how AI-powered mobile apps are impacting business.

Impact Of AI-Powered Mobile Apps on Businesses

“The measure of intelligence is the ability to change,” said Albert Einstein. That is a reality in technology. Growth requires change, and change requires intelligence. AI achieves growth by bringing in that much-needed change in mobile apps.

AI is instrumental in driving innovation in mobile apps. Today many users neglect applications that do not have innovative features. This calls for developers to be on the ball when it comes to facilitating digital transformation with the help of AI.

AI-powered apps are experiencing higher than anticipated demand. According to Fortune, the AI market size is projected to grow from USD 387.45 billion in 2022 to USD 1,394.30 billion by 2029. A staggering figure indeed!

Well, that is not all. Here are some facts that are keeping mobile app developers and publishers on their toes:

• There are over 6.5 billion smartphone users worldwide.
• On average, an American looks at his phone 344 times each day. That is once every four minutes.
• 88% of mobile time is spent on mobile apps, and the app percentage continues to increase yearly.
• 47% of established organizations have applied an AI strategy to their mobile apps.

AI-powered mobile apps can help businesses conquer their market. Let us understand why and how they can prove to be game-changers for top industries.

Top Industries That Can Benefit from AI Mobile Apps and How

Mobile apps allow users to do many things more conveniently, quickly, and smartly. AI-powered mobile apps have turned smartphones into on-the-go computing machines. That is why many top industries leverage it to provide new solutions, engage their customers, and thus stay on top of their competition. Here are examples of five top industries that are benefiting from mobile apps:

1. Ecommerce

eCommerce customers prefer to use retail apps over mobile websites for their shopping needs. Top companies like Amazon increased their sales by engaging with and offering customer deals through mobile apps.

It was also noted that mobile apps somewhat level the playing field for small businesses trying to compete with established businesses in their sector. Mobile apps also increase the probability of customers purchasing more than what they would buy when they visit the website. It is imperative that businesses adopt AI-powered app development as part of their growth strategy.

2. Healthcare

AI applications can build sophisticated machines, analyze chronic conditions and quickly provide medical data to medical staff. Using AI-powered mobile apps in the healthcare industry can minimize in-person doctor visits allowing doctors to quickly and efficiently treat their patients in real-time. They improve the medical facility and expedite services.

Fitness apps have become unbelievably popular after the pandemic. The development of AI-powered mobile apps also encourages people. When fitness apps are merged with health apps, they can measure health parameters like blood pressure and pulse. AI-powered mobile apps can also be synchronized with wearable devices.

3. Education

AI-powered mobile apps allow teachers to create interactive learning materials for their students. Such learning helps the education industry to make learning more fun and interesting. Plus, it beats geographic barriers by enabling students to access educational content worldwide.

It can increase productivity among faculty and permit them to give more attention to their students. AI-powered mobile apps can automate back-office tasks like grading, arranging, facilitating parent-guardian interactions, managing enrollment, and more.

4. Human resource management

AI-powered driven systems can aid in the blind hiring process. Using ML software, HR staff can examine applications based on specific parameters from anywhere in the world. It can scan applicants’ profiles or resumes and provide recruiters with the talent pool they are looking for.

5. Real estate

The real estate industry can benefit from AI-powered mobile apps in a big way. Since most realtors and property owners already use smartphones to rent or buy properties, real estate professionals can use mobile apps to showcase their listings on these platforms. The development of niche applications can help renters to find homes directly through the app.

Read more: How Realtors Are Winning Tenants With Innovative Mobile Apps

How Can You Identify AI Capabilities For Your Company?

No business can afford to sit back and ignore the capabilities of AI-powered mobile apps. However, rushing to adopt AI without thinking it through can be damaging. To fully realize its capabilities, you must approach it with a clear business goal. This means you must narrow it down to your business’s most valuable AI capabilities. How can you do that? Keep in mind these two fundamental steps:

• Identify potential use cases of AI-powered applications in your business
• Sort those potential use cases into just a few top priorities.

How Can Fingent Help?

The possibilities for business growth through AI-powered mobile apps are endless. Fingent is an expert when it comes to AI-powered technologies. We specialize in implementing your solutions into the mobile environment.

We have delivered successful projects globally. Here are three case studies:

1. Ambit

Ambit is an AI machine learning program that simplifies a time-consuming worker’s compensation process that usually takes up to three years. Among several other benefits, this solution offers insurers a 57% reduction in costs. Combining AI with the client’s litigation strategy, Fingent helped develop a solution that now cuts the average case settlement time to 1-2 days at a settlement cost of $15000.

2. AI-powered chatbots

As their technology partner, Fingent helped the University of North Carolina (UNC) develop an automated intelligence-driven ecosystem that facilitates seamless interaction between students and their instructors utilizing AI-powered chatbots. Enhanced learning is made possible by employing a Watson-powered Teaching Assistant (AiTA).

Read more: Using Chatbots to Create an Enhanced and Engaging Learning Experience

3. MUSA

Fingent developed MUSA, an AI-powered virtual assistant, to improve in-house HR teams’ response time. This minimized their workload as MUSA took over the management of routine tasks and gave the HR team more time to focus on their core function.

Top benefits of the solution:

• Improved the HR team’s response time.
• Automation of Frequently Asked Questions (FAQs) minimized workload considerably.
• Helps provide instant and accurate responses to common queries.
• Improved ability of the HR team to handle more complex queries and circumstances.

With a highly efficient team of experienced developers, Fingent custom software development experts are committed to understanding your business needs, using the latest and most advanced technologies to work out the perfect solution for you, and working tirelessly to deliver high-level apps that will transform your business. We have delivered successful projects globally. We are known to offer robust, cost-effective, and customer-centric mobile applications to enterprises and startups.

Give us a call, and let’s discuss how these capabilities can help your business.

Machine learning is changing the face of everyday life, science, and business. It is revolutionizing all industries, from advancing medicine to powering various cutting-edge technologies. Though Machine learning (ML) was a part of AI’s evolution until the 1970s, it evolved independently. It has become a chief response tool for cloud computing and eCommerce.

The goal of machine learning in business is to adapt to new data independently and make decisions and recommendations based on thousands of analyses. Machine learning enables systems to learn, identify patterns and make informed decisions with minimal human intervention.

Today, ML is a necessary aspect of modern business. It uses algorithms and neural network models to improve the performance of computer systems. Machine learning in business and manufacturing is enabling organizations to achieve notable strides. These strides include increased performance and efficiencies, improved processes, and enhanced security.

This article will discuss the benefits of machine learning in business and its use cases.

Remarkable Benefits of Machine Learning for Businesses 

According to Fortune Business Insights, the global market size for machine learning in business is expected to grow to USD 209.91 billion by 2029, exhibiting a CAGR of 38.8% during the forecast period. ML has been and continues to scale operations tremendously. Across industries, ML has led to a boom in affordable data storage and faster and more reliable computational processing.

Here are six remarkable benefits of machine learning in business:

1. Automation for better decision-making 

Most businesses find themselves wasting precious time sorting through duplicate and inaccurate data. Such businesses benefit from using the predictive modeling algorithms of ML in their processes. Such a process will understand duplicate inaccurate data and distinguish the anomalies. It enables the organization to avoid inaccurate reporting that can result in poor customer retention.

Instead, this will allow businesses to use their accurate database to detect wasted costs, missed opportunities for sales, and revenue capital. In addition, organizations can overcome challenges and risks that arise due to miscommunication or poor performance metrics. Thus, businesses can streamline their operations and improve decision-making which could be translated into better ROI.

2. Increased scalability with minimum expense

Semi-supervised machine learning algorithms can help organizations leverage useful insights from customer profiles and enable them to view their brands from customers’ perspectives. Doing so will equip organizations with relevant insights to build their brand by improving their products and services.

3. Predictive maintenance

Predictive maintenance that ML aids manufacturing firms’ power to follow best practices that lead to efficient and cost-effective operations. The historical and real-time data predict problems and stipulate strategies to solve those problems. Plus, workflow visualization tools can eliminate issues and unwanted expenses incurred due to those issues.

4. Financial analysis

ML can greatly assist as it gathers and analyzes large volumes of quantitative and accurate historical data. It is used for portfolio management, loan underwriting, fraud detection, and more.

5. Personalization 

Using machine learning in business will allow organizations to know their customers better and provide them with a more personalized customer experience. Organizations no longer need to rely on guesswork because ML models can process different types of information collected from numerous sources and provide relevant data about their customers.

6. Cybersecurity

ML technologies can improve cybersecurity to solve cyberattacks once and for all. Empowered by ML, intelligent security programs can gather and process data about cyber threats and respond to them in real time. ML models can detect the slightest deviations in patterns and flag them. Or destroy an attack in its nascent stage.

Read more: Can Machine Learning Predict And Prevent Fraudsters?

Top Use Cases

Machine Language has made its mark across industries and found a place in many different applications. Here are some top use cases:

1. Enhanced social media features 

Businesses can use machine learning algorithms to create attractive and effective social media features. For example, ML algorithms in Facebook enable it to identify and record a person’s activities. These activities include records of chats and the amount of time that person spends on each post. It uses this data to determine what kind of friends and topics may interest that person and accordingly make suggestions.

Read more: Why Time Series Forecasting Is A Crucial Part Of Machine Learning

2. Product recommendation

Product recommendation is an advanced application of machine learning techniques. It has been the most popular application of almost every eCommerce website today. This technique allows websites to track a consumer’s behavior based on their previous purchases, search patterns, and cart history. It enables the website to make apt product recommendations to that consumer.

3. Recognition

Image recognition is one of the most significant and notable ML and AI techniques. It is adopted further for pattern recognition, face detection, and face recognition.

4. Sentiment analysis

Sentiment analysis is a real-time ML application. It determines the emotion or opinion of the speaker or the writer. For example, a sentiment analyzer can detect the thought and tone of a written review or an email. It can analyze the review-based website, decision-making applications, and more.

5. Access control

Most large businesses are actively implementing ML models to determine the level of access an employee should be granted. This application of machine learning can ensure the security of the organization.

6. Bank Domain

Banks are using ML to prevent fraud and protect accounts from hackers. Machine learning algorithms determine what factors to consider in creating a filter to prevent an attack.

Read more: Machine Learning – Deciphering the most Disruptive Innovation

How Fingent Can Help with Deploying the Best of ML

Leveraging the capabilities of machine learning in business can open the door to many opportunities. It is wise for any organization to take advantage of ML rather than lag behind competitors. However, we understand if you have questions. That’s why Fingent software development experts are here to help you. We can deploy the best machine-learning models efficiently and smoothly.

As a partner, Fingent can work with your team as you take on digital initiatives for sustainable business growth. We enable our clients to make data-driven decisions by efficiently deploying machine learning in business. Our cost-effective services will save you a considerable amount of time and money.

Furthermore, we do not follow a one-size-fits-all strategy. We provide custom software development services that cater to your needs. Therefore, look no further if you are looking for a reliable, efficient IT partner to deploy the best machine-learning models.

Contact our experts today!

From the mundane to breathtaking, AI is disrupting virtually every business process in all sectors. People are ceasing to associate Artificial Intelligence with science-fiction dystopias as Artificial Intelligence (AI) is taking more commonplace in our daily lives.  While such acceptance in mainstream society is a new phenomenon, it is not a new concept in business. Today, AI has become imperative to maintain a competitive edge.

This guide will help business owners who are serious about maintaining a competitive edge in their business sector by adopting AI.

Rising Need for Adopting AI In Business

Did you know that 52% of companies accelerated their AI adoption plans after the pandemic? Why?

Artificial Intelligence in business is seen as a supporting tool. It is adept at processing and analyzing a trove of data much faster and more efficiently than a human brain can. Since AI can synthesize courses of action and present them to the human user, businesses can use AI to help investigate the probable consequences of each action. That way, businesses can streamline the decision-making process. This is what makes AI valuable throughout many industries.

Artificial Intelligence is a form of software that can make decisions independently. It can act even in situations not foreseen by programmers. AI has a wider latitude of decision-making capabilities than traditional software – whether it is simply helping visitors or performing a task as complex as monitoring a wind turbine to predict its maintenance.

Read more: Conversational AI: Reimagining Customer Experiences

How To Identify If Your Business Needs AI?

AI software and tools can make business processes much simpler and more effective. Besides, implementing AI in business ensures cybersecurity defense, powers customer service, and more. But how do you know when you must adopt AI in business? Here are a few scenarios:

Scenario 1: Do you need to enhance your customer experience? 

Are you struggling to provide your consumers with quick, easy, and personalized solutions? AI-powered digital assistants can help your business resolve customer queries by imitating human conversation. Chatbots are among the most promising trends in customer engagement and customer experience. Perhaps most business owners realize how imperative this AI technology is to their business. Perhaps that is why the chatbot market is set to reach 1.25 billion USD by 2025.

Scenario 2: You know the value of sentimental analysis but do not know how to leverage it.

Businesses use sentimental analysis to monitor and analyze customers’ opinions and emotions from various texts on a website, social media, and product or service comments. Skimming through large amounts of data to churn out customers’ sentiments can be daunting. All thanks to AI-assisted sentiment analysis, you can now quickly understand how your customers feel about your services or products.

Scenario 3: Your business has suffered due to inaccurate forecasting.

Accurate sales forecasting helps businesses predict future sales for long-term business growth. It can also enable the detection of potential problems to avoid them. Implementing AI-based CRM software can help detect how each data element relates to sales performance.

Scenario 4: You have a great online presence but an awful in-store experience.

If that describes your business, it is time to adopt AI to provide the next level of a personalized in-store experience. AI can enable instant access to products or services and contribute to smarter buying decisions.

A Quick Guide to Implementing AI For Your Business

AI applications can be used in many ways depending on organizational needs and the business intelligence (BI) insights derived from the data collected. Here are some tips to explain the steps businesses can take to ensure their implementation is a success:

1. Know your options.

Find out your options and what AI can and cannot do. This will help you decide if you want to add specific AI technology or change the entire app.

2. What is your business goal?

Working on an ‘end-first’ process will help refine the list to select specific features or capabilities that best suit your business goals.

3. Find out how AI can benefit the end-users

This is crucial as it gives you the two main objectives for a successful implementation. Then, choose the software and hardware you need to make this process a reality.

4. Evaluate your internal capabilities

You need to consider if you have enough skilled employees in-house who can manage the process and if you have the budget to outsource it.

5. Choose between building or integrating the system

Remember building an AI system from scratch can take several months. On the other hand, if you choose to use a premade system, your AI partner will help install the software app, train your staff, and fulfill your business needs.

6. Test system

Testing the system for a predetermined time will help you understand if the clients are more satisfied, and if the employees work more efficiently.

7. Choose the right partner 

A good AI partner will be clear about the offer, value, and terms of cooperation.

8. Make refinements

After you gather a reasonable amount of data evidencing the success of an AI solution, you can start making refinement changes to the solution.

Watch more: How Artificial Intelligence Can Enhance Your Customer Experience!

Avoid 4 Common Mistakes While Implementing AI

A well-considered plan can lead to success, but a mistake can cost you considerably in terms of time and resources. Here are four common mistakes to watch out for when implementing AI:

• Not applying AI to the right use cases: If AI is incongruous with your business goals, your time and resources will be wasted

• Not diligent in hiring the right talent: Hiring the right AI team is like putting together the right football team that can win. Hire candidates with specialized skill sets and experience that match your business needs.

• Ignoring data: Ensure all teams are responsible for organizing, vetting, and maintaining data.

• Inadequate intervention: Inadequate intervention could result in AI recommendations that hinder business objectives. Hence, ensure interventions are scalable and repeatable.

How Fingent Can Help You With Personalized AI Software Development 

Artificial Intelligence is for every future-oriented business. How exactly you will use AI depends on your business goal and how well it was implemented. At Fingent top custom software development company, the AI developers are equipped to design intelligent solutions to help solve your business problems, automate tasks, and improve customer experience.

Our suite of AI solutions includes data capture and processing. Our AI developers are also proficient in analytics, multi-platform integration, and ML solutions.

Let us help you reach your business goal with intelligent AI-driven solutions. Give us a call today.

The strategic significance of advanced technologies as a critical business component is recognized by enterprises like never before. Besides business modernization and cost reduction, advanced technologies allow you to compensate for labor shortages, improve brand value and competency, and expedite research and innovation processes. However, several companies jump onto the bandwagon without properly understanding the practical applications and benefits of advanced technology in their business. Only 23% of small and medium-sized enterprises (SMEs) worldwide can invest in and grow with new digital tools, indicates the World Economic Forum. This data proves why companies should analyze advanced business technology examples before adopting digital tools.

Read more: Using technology to build customer trust: Your business plan for 2022

To simplify your understanding, here’s a quick rundown of five advanced business technologies we believe will help you cope with the new business and economic environment. 

• Simplifying Workflows With Cloud
• Low-code Applications
• Robotic Process Automation (RPA)
• Document Data Extraction
• AI Assistants

As these business technologies become more affordable and handy, businesses are ardently pursuing them to automate customer service, streamline workflows, differentiate products and services, and reach new markets. Depending on your budget, implementation timeline, priorities, and unique business requirements, our team at Fingent helps you build the roadmap for technology adoption. 

Let’s take a closer look at the five inevitable technologies for business transformation today:

Read more: How to gain maximum value from your technology investments?

1. Simplifying Workflows with Cloud

Workflow management is a highly overlooked enterprise strategy that directly impacts productivity. Managing different stakeholders, heaps of confidential data, and a series of preset and conditional tasks manually can lead to several errors such as employees missing key steps, policy violations, compliance issues, and monetary losses. By taking your workflows online, cloud-based workflow management applications increase your productivity. 

Cloud-powered workflows or workflow management tools:

• Are scalable, centralized, customizable to your needs, easy to integrate, secure, reliable, and hassle-free. 
• Offer a seamless and unified collaboration interface by preventing users from toggling between different messaging apps or communication channels.
• Reduce your dependency on in-house IT team by passing on the software maintenance responsibilities to the third-party software vendor. 
• Can be accessed via any authorized network (with approved access credentials), on any device, from anywhere, 24/7. This has been a huge game-changer for several companies that switched to remote operations during the pandemic. 

Example of a Cloud-based Workflow Tool

Finding a cloud workflow management tool that can be customized to your company’s requirements is daunting. The platform should integrate well with your organizational processes without disrupting your existing workflow. This is where digital workplace applications like InfinCE make the difference. 

With InfinCE Digital Workplace, Fingent has improved its productivity by 20% through real-time, effective, and easy collaboration. Data-powered dashboards, dedicated servers, collaboration apps, productivity tools, virtual desktops, private mobile apps, and a host of exceptional business management features enabled us to achieve a significant operational breakthrough in streamlining workflows. 

Read the full case study here.   

2. Low-code Applications

Gartner estimates that by 2025, 70% of enterprise applications will use low-code or no-code technologies. Digital business transformation requires pushing custom software solutions to the market at lightning speed. This demand has given rise to low-code applications that will break the technological and organizational silos of application development, automation, integration, and governance. Low-code development enables business users to bring innovative ideas to life by just dragging and dropping low-code elements through a graphical user interface. 

In simple words, low-code development enables “citizen” developers or non-tech users (such as business analysts or marketers) to build dashboards and survey or contact forms faster. Professional developers, on the other hand, can leverage low-code techniques to perform more efficient tasks such as legacy application modernization or back-end integrations with improved agility and velocity.

Use Cases for Low-code Applications

• Customer engagement applications and portals
• Mission-critical applications such as ERP software, payments manager, etc.
• Data analysis applications, BI dashboards, and data management software
• Mobile apps for customer engagement
• Order processing, inventory, order fulfillment, supply chain, and accounting apps

Salesforce Lightning, Microsoft Power Apps, and Zoho Creator are some of the leading low-code applications today. SAP users can leverage the unified low-code/no-code (LCNC) solutions on SAP Business Technology Platform (BTP) to rapidly build and extend applications, and automate tasks and processes.

3. Robotic Process Automation (RPA)

Robotic Process Automation (RPA), often referred to as software robotics, is an easy-to-use software technology that allows anyone to automate digital tasks within their business processes. RPA allows users to create software robots or “bots” that can learn, emulate, and then execute rules-based business processes. According to Forrester Research, RPA software revenue is expected to reach $6.5 billion by 2025, while RPA-related services revenue could hit $16 billion in the same year. 

Potential Use Cases for RPA 

We offer free proof of concepts to help you understand how RPA can improve your business efficiency and customer experience. Some of our top use cases include:

• Automating discharge protocols and data management to increase HR productivity in healthcare.
• Daily retail process automation such as order processing, inventory and warehouse management, etc. to save time and resources.
• Reducing customer wait times through RPA-enabled chatbots that answer customer queries in real-time. 
• Error-free, automated billing and invoices to keep your financial systems and reports up-to-date.
• HR teams can automate the maintenance of personnel data and records, streamline onboarding, and manage payroll seamlessly. 

Download our white paper to learn more about how Robotic Process Automation can simplify your business operations

4. Document Data Extraction

Extracting quality data out of unstructured or poorly structured data sources and documents for further processing, migration, and storing has been a biggest obstacle in automating back office operations. If you are entering structured invoices to a robust ERP tool like SAP, your payments can be automated and system records can be generated automatically. Due to the high costs of data extraction, several businesses extract only critical information fields, for example, the payment field within an invoice. Businesses are compelled to manually extract data from other important fields, such as validating the invoice’s compliance with VAT.  

AI-integrated OCR Software for Document Extraction

Optical Character Recognition (OCR) is an affordable, game-changing technology that automatically extracts data from the digital images (photos) of large files, scanned documents, and sub-titles or captions superimposed on an image. It reduces the time spent in manual data entry and extraction by automatically converting typed, handwritten or printed text into machine-readable text. AI-powered automated data extraction tools like DocuSign, Docsumo, Kofax Capture, and Amazon Textract leverage OCR technology to reduce the chaos involved in document data extraction and enable businesses to create an efficient workplace. 

Our team helps customize document data extraction software that can save your time and money by eliminating transcription and transposing mistakes.

5. AI Assistants

One of the most common examples of small business automation today is the use of AI-powered virtual assistants. They can save your employees’ productivity by automating the most repeatable customer interactions, such as technical support, appointment scheduling, lead qualification, and order management. AI virtual assistants like Google Assistant and Alexa can understand and act according to your voice commands and customize responses to your queries. Understanding customer intent through natural language processing and recognition allows AI assistants to maintain a human-like conversation.

Chatbots are a popular category of AI assistants that are designed specifically for text-based channels like SMS, email, and live chat. Recent years have witnessed a rise in chatbot adoption among several business verticals, product and service lines, websites, mobile apps, customer portals, and so on. Data shows that 58% of B2B companies and 42% of B2C websites are using chatbots to make their websites and mobile apps more interactive. More than 56% of businesses believe chatbots to be driving digital disruption in their industry. 

Case Study: AI Virtual Assistant for HR     

Fingent’s HR team was pressed to transform their service delivery model as routine, transactional tasks affected their performance and efficiency. To solve their struggle, Fingent developed MUSA, an AI-powered virtual assistant (a chatbot) and integrated it with Fingent Hub, Fingent’s internal employee management system. MUSA is short for Multi Utility Assistant. Employees can ask MUSA any queries related to HR and IT DevOps processes at Fingent, and they’ll get answered instantly. MUSA has improved our HR team’s response time by minimizing their workload and allowing them to focus on areas requiring more attention.     

Read the full case study here.

Business and Technology Are Inseparable

Gartner writes that businesses leading with technology employ advanced tech to boost their customer experience and revenue growth, have a clear understanding of their priorities, goals, and strategies, and invest in solutions tailored to their needs. Technology allows businesses to lower the walls within and between their organizations, customers, providers, suppliers, and so on. Organizations perceiving technology as a key business consideration will be able to match the pace of business change and stay relevant and competitive. 

How can your company embrace growth in a new era of transformation and business technology trends? If you feel you’re getting caught in the technology maze, take a quick break to contact us.

Our consultants can simplify your technology adoption strategy based on your priorities, customer needs, financial resources, and technical requirements. 

Old is gold … but is it? There are some things that get better with age of course, but when it comes to software, it’s a hard NO.  

Business after Covid is not the same as when you started it. So, using legacy software to run your business is like using bullock carts for transportation even when bullet trains are available. 

True, there are some systems that are hard to be replaced. On the other hand, there are some that need to be modernized or even completely scrapped. One of these is legacy software. Nevertheless, the modernization or replacement of legacy software is not always defined by its age. It might be that it is no longer relevant to the current business strategy and goals. When such software becomes difficult to maintain and improve, it is time to pivot to the platform ecosystem. 

This article discusses the benefits of pivoting your legacy software into a platform ecosystem. Before that let’s understand when and how a company should consider pivoting to the platform ecosystem.

Let’s start by understanding what a platform ecosystem is.

Read more: 5 Ways Application Modernization Enables Your Business to Grow and Reap ROI During a Pandemic

What Is Platform Ecosystem?

A platform ecosystem is a connected system of companies that share large amounts of data with a common goal. When executed well, it has a massive impact on solving societal challenges successfully establishing and launching a viable ecosystem. 

When Should a Company Consider Pivoting to AI-enabled Platform Ecosystem?

Legacy software may have been useful in the past. Today, you no longer see enough ROI. The longer you allow it to interfere with your business, the more resources you will have to devote to keep your current system functioning. 

After all, any company would expect to profit while ensuring to invest in the right places. Recognizing the obvious downsides will help you understand when and why you must pivot to the platform ecosystem. Here are three examples that increase the cost of running legacy software:

1. Maintenance cost

Overhead cost: When your legacy software needs constant patching and repairs, your overhead costs can increase exponentially. 

Human resource: If your team spends most of their time on maintenance, they will be distracted from higher-value projects that can contribute to increased ROI.

2. Cost of Integration

Integrations: You may feel tempted to look for workarounds that allow your system to work with current software and hardware. This can lead to reinventing your entire system. Essentially, you will be left with a lot of new patches on the old system that can increase your integration cost and maintenance costs. 

Equipment: You will have to retain some of the old software and hardware because of compatibility issues. Maintaining such old equipment also can increase your cost in terms of money and human resources. 

3. Cost of brand image

Customer retention: Because legacy software may become cumbersome and slow for today’s fast-paced customers, they may move on to your competition. These customers may include some of your loyal customers who lose patience. Gradually, such loss of customers will diminish your market share. 

Brand reputation: Cumbersome legacy software can change the way your existing customers and the general public view your brand. Remember, if it costs your reputation, it will cost your business!

Read more: Why modernize your legacy systems. What is the best approach?

Steps to Pivot Your Legacy Software

Steps to pivot legacy software to a platform ecosystem vary from business to business. But there are common threads in how they can approach this journey. The companies wishing to grow with AI-enabled platforms must carefully assess and plan the transition. Doing so will ensure long-term success.

1. Assess and document your current software

Analyze and document how your current software fails to meet your business needs. Such analysis will help you understand what you need. 

Create a journey map to visualize the UX and CX of your legacy system. Find out how your partners, customers, and stakeholders are using your current system. 

This is a preliminary step so do not rush through your assessment. A thorough review now can provide you with a clearer picture of your journey and save you much time and resources during the journey. 

2. Find out the right strategy for your organization

Some of the strategies you could consider are replace, rebuild, rehost, and re-platform. The right strategy depends on various factors including the expected ROI, the timeline, and more. It is important to get your stakeholders involved in this step. 

3. Access to partners’ data

Access to partners’ data plays a huge part in driving value. Ensure to include access to partners’ data. Also, ensure this relationship comes with the ability to use AI models like customer matches and recommendations. 

4. Create an interface and a timeline

Ecosystem partners need access to AI data and decisions. This is made possible by creating an API architecture. API network allows providers to interface with the company. 

When mapping out your journey, factor in the time you will need to locate any other resources and the current projects your team is working on. 

5. Identify and gather

Most decisions are made by AI. Hence, Identify the key decisions that you would want AI to make and then use that data to train the models.

6. Design and implement a smooth process

The frictionless platform model can simplify the process for your customers.  Work with your partners to design and implement a seamless process that meets your customer needs. 

7. Data is power use it wisely

The machine learning process will continue to improve as they make decisions, and they will get better at predicting or recommending. Retrain them as soon as you source new data. You can also train them when you notice that they are not doing their job very effectively. 

8. Begin implementing your project plan

Once you start implementing your project plan, ensure to keep all lines of communication open and clear. Sharing information across the team about changes will help prevent problems.

Advantages Of Pivoting to Platform Ecosystem

The primary value of the platform is to grow your business. It is also useful for gathering data to train AI models. Each new member of the ecosystem provides more value to the network and more data. As result, you will have better AI models. 

Data powers AI-enabled decisions in order to quickly and efficiently process claims for your customer. In a platform ecosystem, companies work together towards a common goal. They create value for each other and their customers.  Clearly, new technology delivers a bigger return than keeping the existing software. At Fingent, we work with our clients to make this transformation smooth and seamless. 

Give us a call and allow us to help you effortlessly pivot your legacy software into a platform ecosystem.

The popularity of edge computing and artificial intelligence (AI) has risen in recent years due to the widespread adoption of mobile technology and the Internet of Things (IoT) by various industries. The Linux Foundation’s State of the Edge Report 2021 predicts that the global market capitalization of edge computing infrastructure would reach $800 billion by 2028. If edge computing garners a wider attention span, the number of enterprises investing in AI is also growing year over year. According to the State of AI 2021 Report, the global AI funding witnessed a whopping 108% increase in 2021. More than 54% of the organizations surveyed by McKinsey in 2021 said that they have adopted AI in at least one function. 

Individually, both AI and edge computing help businesses in incredible ways and hold immense potential for future development. Many forward-looking organizations are investing in these two technologies as part of their digital transformation journey. “Two heads are better than one”, goes the saying. True to this, many enterprises and technology champions are discovering new opportunities by combining edge computing and AI, or Edge AI. In this blog, we’ll see how edge computing and AI are being put to work together and discuss some use cases that will take AI applications to the edge.   

Read more: Future-proof your business with 5G, edge computing and cloud

What is Edge Computing?

Edge computing refers to a distributed computing framework that brings the deployment of computing and storage resources closer to the data sources, such as local edge servers or IoT devices. By bringing enterprise applications closer to the data sources, edge computing offers a multitude of business benefits; including faster data processing and insights generation, better response times, and enhanced bandwidth availability.  

In edge computing, all your device-generated data is processed and analyzed close to the source where it’s created. By preventing your data from traveling over a network to a centralized or cloud data center, edge computing reduces latency and improves bandwidth availability. 

Example: Electric vehicles (EVs) leverage edge computing for data aggregation and insights generation, which help optimize charging stations and monitor the health of EV batteries.  

Read more: 9 examples of artificial intelligence transforming business today

What is AI?

Artificial Intelligence or AI refers to machine intelligence, where a computer-controlled (software-programmed) machine simulates human intelligence to perceive its environment and take corresponding actions that help the machine achieve its goals. AI uses machine learning and deep learning techniques to churn robust input datasets (labeled training data) and enable rapid problem-solving. 

The content recommendation systems used by Amazon, Netflix, or YouTube and Google’s advanced web search engine are some of the leading examples of AI today. The growth of artificial neural networks and deep learning technologies enable AI systems to process massive amounts of data at an incredible pace and predict future states with exceptional accuracy.     

AI-powered applications command a larger share in today’s enterprise landscape. AI helps banks, insurance companies, and financial institutions with fraud detection. AI is being used by conversational bots to enhance customer service. Smart assistants like Siri and Alexa leverage AI to improve customer experience. Hospitals and healthcare providers use AI-embedded applications for making clinical decisions and delivering remote patient care. 

Case Study: MUSA, Fingent’s AI-powered virtual assistant minimizes day-to-day workplaces struggles related to PeopleOps and DevOps. Read Now! 

Edge AI: The Next Wave of Enterprise Digital Transformation

AI applications give the intended results by relying on seamless data transmission and computation of complex ML algorithms. Edge computing helps move AI systems close to the source where the data is generated. When AI computation is done at the edge of the network, next to the data source, it gives more accurate and desired results. This process has given rise to a new computing paradigm: Edge AI.

In edge AI, both data generation and computation take place at the network’s edge, instead of sending and processing data in a faraway cloud computing center. Here, “edge” of the network could connote anything – mobile devices, retail stores, factories, hospitals, medical equipment, traffic lights, autonomous vehicles, and so on. 

Read more: Quantum vs. Neuromorphic Computing: What Will the Future of AI Look Like? 

Here’s how your business can benefit from the adoption of edge AI: 

1. Low-power, offline capabilities

Traditional AI applications require enormous amount of processing and computational power to operate some of the complex ML algorithms. Distance from the cloud servers often affects the deployment of AI systems in remote locations. Edge computing helps overcome this challenge as the technology is designed to operate in low-power, offline environment. For instance, blockchain and smart contracts that rely on decentralized ledger technology (requiring no central broker or mediator) can independently run on computation-heavy AI algorithms within the edge devices.

2. Faster computing and real-time insights

Edge AI enables your applications to respond to users’ requirements in real-time. This is because edge computing analyzes data locally, close to the source where it’s generated, instead of a remote cloud data center, which usually delays responses due to long-distance communications. 

3. Better data security

If AI ensures the privacy of data that needs to be analyzed by securing if from getting exposed to cyber miscreants, edge AI adds an additional layer of privacy by containing that data locally. Edge AI uploads only the insights and analysis to the cloud and even anonymizes the data uploaded for training purposes to protect user identities. Thus, edge AI enables businesses to ensure data regulatory compliance. 

4. Constant improvement

AI models can improve their accuracy when they get access to more training data. When an edge AI application confronts data that it is unable of processing, the application will upload the data so that it can retrain and learn from it. Since the new data set is captured right at the production edge (without any transmission delays), the edge AI application will quickly learn from the new data, ensuring constant improvement through learning.   

5. Cost reduction

Offline capabilities and decentralization enable Edge AI to process data without larger internet bandwidths. This reduces your networking costs significantly. Enhanced performance of AI-enabled applications keeps your operating costs down. 

Potential Use Cases of Edge AI

The rapid growth of intelligent applications and the increasing enterprise workloads on cloud are driving the adoption of edge AI. The edge AI software market is estimated to be worth $1,835 million by 2026, states a recent study. The amalgamation of edge computing and AI has led to many breakthrough advancements in recent years. Here’re a few potential uses cases of edge AI:

Healthcare

AI-powered medical devices and instruments at the edge deliver on-demand insights for clinicians to make crucial and faster decisions about patients. During surgical procedures, surgeons can rely on the ultra-low latency surgical videos streamed into AI-powered medical data processing applications to quickly detect abnormalities and identify chances of excessive bleeding. Devices out of the operating room, such as CT and MRI imaging scanners, DNA sequencers, cryo-electron microscopy, and other life science instruments also benefit from edge AI. 

Energy and utilities

Edge AI models can leverage past insights, weather patterns, grid conditions, and other crucial meteorological information to create advanced simulations that help define new ways to improve the generation, distribution, and management of energy resources. This facilitates intelligent forecasting in the energy sector, which helps prevent discontinuous power and energy supply affecting the day-to-day lives of people.  

Manufacturing

Edge AI applications can collect data from sensor-enabled devices installed across the factory floor and process the same in real-time, with ultra-low latency. This advantage gives rise to new use cases in manufacturing and distribution, where real-time and rapid data processing is required. Examples include detecting workplace hazards, finding product defects in assembly lines, flagging machines that require attention or human intervention, and more.  

The list of edge AI use cases keeps growing every day. Smart virtual assistants, voice commands that replace text-based searches, autonomous vehicles, self-driving cars, video surveillance, motion detectors, and industrial IoT security are a few typical use cases that could be enhanced through the integration of edge AI. Fingent helps build faster, reliable, and cost-effective enterprise applications powered by edge and AI.

Are you ready to explore the possibilities of Edge AI in your business operations? Contact us today!   

There couldn’t be any better empirical evidence than COVID-19 to prove the transformational impact of AI on healthcare. Had AI not been there, it would be unviable to develop and distribute vaccines at record speed, empower public health officials and front-line workers, support equipment manufacturers, take critical life-saving actions, and respond to these abnormal times. 

Leading pharmaceutical company Moderna relied on automated processes and AI algorithms to rapidly bring out their covid vaccine nominee for its first clinical trial. From an anticipated 15% chance of success, AI helped the pharmaceutical company lift their success rate to a whopping 50%, placing the vaccine efficacy levels close to 94.5%. AI’s role in healthcare isn’t limited to pharmaceuticals alone.

In this piece, we’ll see what AI holds in store for healthcare now and in the coming years.   

Read more: AI in Medicine – Yesterday, Today, and Tomorrow

Top Applications of AI in Healthcare

Over these years, AI has brought more sophistication into what humans do, particularly in segments like healthcare. Here’re a few AI healthcare transformations currently underway:

1. Allows People to Stay Fit

AI and the Internet of Medical Things (IoMT) have helped launch several consumer health applications and self-health monitoring devices such as wireless-enabled wearables, activity trackers, pedometers, smartwatches, and other physical fitness monitoring gadgets. These healthcare technology applications encourage people to take proactive measures for maintaining a healthy lifestyle and allow consumers to be in control of their health and well-being. Similarly, healthcare professionals can rely on AI to better understand what their patients need. With insightful patient data, caregivers can provide the necessary guidance and support, thereby enabling people to stay healthy.  

Read more: 5 Healthcare Digitalization Trends Crucial in 2022 and Beyond 

2. Early Disease Detection

It’s well established that the early detection, screening, and treatment of cancer can improve outcomes. American Cancer Society is successfully using cloud ML engine on Google Cloud Platform to analyze breast cancer images with 12x improved speed. Advanced deep learning models are being used to detect Diabetic Retinopathy (DR) during the early and asymptomatic stages. This helps save diabetic patients from the daunting issue of irreversible blindness caused by lesions on the retina. The proliferation of consumer wearables and self-health monitoring devices, combined with AI allows doctors and caregivers to detect potentially life-threatening ailments at more treatable stages. 

3. Medical diagnosis 

The market value of global AI in medical diagnostics is estimated to be worth $3988.0 million by 2026. Leading AI platforms such as IBM Watson Health and Google DeepMind Health enable a large number of healthcare organizations to unlock massive amounts of clinical data to boost medical diagnosis. 

Combining machine learning and neuroscience, AI helps build powerful neural networks that are capable of imitating human abilities. Watson can review and store huge volumes of medical data scattered across journals, seminars, conferences, treatment case studies, and umpteen other sources. AI’s ability to ingest enormous amounts of data, decipher images, and discover hidden patterns escaping even the most-canny human eye are expected to significantly transform healthcare in the near future. 

Read more: Deploying Digital Twins in Healthcare

4. Clinical Decision-making

In the past, clinical decision support systems (CDSS) were fed by inaccurate datasets that led healthcare professionals to make flawed assumptions. Diagnostic errors are one of the top reasons behind higher mortality rates and prolonged hospital stays. Thanks to AI, ML, and the growing volumes of real-time clinical data gathered from numerous healthcare apps and devices. Clinical decision-making is now more precise and efficient with the emergence of AI-powered CDSS. 

Sepsis Watch, a deep learning tool installed in the emergency department of the Duke University Health System has considerably lowered sepsis-induced patient deaths. The tool flags sepsis patients who are at medium to high risk, allowing doctors to identify early signs of sepsis. Not only does AI reduce diagnostic errors, it also suggests the best practices for post-surgical care and patient discharge, as well as recommends medications and follow-up checks to optimize patient care.  

5. Medical Research and Training

The average cost of bringing a pharma product to the market is exploding year over year. Manual R&D processes and the time taken to conceive, design, and conduct clinical trials slow down drug production and increase the costs involved. The latest advances in AI help streamline drug research and discovery and reduces the time to market for new drugs. Researchers can use AI-enabled simulations on their devices to explore the impact of new therapies or medicines, thereby reducing the risk of testing in live conditions. 

AI allows training and quick catch-up sessions to be held from anywhere, even after a medical resident leaves the campus post a tricky clinical case. AI-powered chatbots can answer queries on the fly, at any hour of the day. With instinctive AI diagnostic support and a low level of supervision, the next generation of medical students will definitely rely on automated self-learning platforms. 

Read more: How Virtual Reality Improves the Standard of Medical Education and Training

Most-anticipated AI Innovations in Healthcare!

Real-time data, technological advancements, and innovation are driving the industry forerunners to discover new AI opportunities in healthcare. Here’re a few healthcare AI innovations to behold in the coming days.

1. Address the Shortage of Physicians

Google is running experiments to develop transformative AI imaging and diagnostic tools that can assist clinicians and even address the dearth of talent in a possibly grueling situation (like the global pandemic). Further research is being held to improve the detection of breast and lung cancer, sight-threatening eye conditions as well as skin diseases.   

2. Genomic Analysis

Research proves that 30% of individual health effects are congenital. All of us carry 4 to 5 million genetic variants, each of which can influence our health traits. The cost to sequence a genome and poor sequencing data have marred genomic analysis in the past, preventing clinicians from identifying genetic disorders and high-risk diseases at an early stage. Deep neural networks such as DeepVariant exhibits top-class accuracy in analyzing genetic variants and sequencing genome data. 

3. Decentralized Clinical Trials

The advent of AI is helping medical researchers and pharma companies worldwide to reduce in-person assessments in clinics. Various digital endpoints, such as smartphones, healthcare software, wearable sensors, EHRs, video conferencing, and numerous physical fitness monitoring devices are being used to gather data with the patient’s consent. This has drastically shifted medical trials from clinics, thereby reducing the risk of compromised immunity, exposure to fatal viruses, respiratory or cardiac malfunction, and other lethal health risks. Decentralized clinical trials allow institutional and federal health boards to review existing processes, implement new regulations quickly, listen to feedback and concerns, take proactive steps, and make healthcare more accessible to everyone.    

AI is Pivotal to Healthcare New Normal

Necessity commands invention. Over the past two years, we saw how healthcare stakeholders around the globe took efforts to harness AI technologies – for discovering new drugs, extending the capability of existing drugs, reducing the time to distribution, screening for COVID-19 symptoms, supporting clinical decisions, automating hospital operations, and so on. Key U.S. healthcare decision-makers surveyed by Intel stated that their trust in AI in processing medical records has increased by 67%. As AI gets infused into more crucial areas of healthcare, it’s important to earn customer confidence and comfort, and support from various stakeholders in the ecosystem.   

Fingent helps develop innovative, AI-integrated, custom healthcare software applications to improve your competitive advantage, time-to-market, ROI, and clinical precision. As the world enters a new era of health, it’s important to choose the right technology partner that helps adopt the right technology at the right time. We have an eminent list of healthcare clients, including NHS, Novita Healthcare, Mundipharma, and Casenet, LLC among others.

Contact us to understand how we’re helping businesses build trust and deliver sustained outcomes by making the most of our experience and technology. 

Language gives power. Using NLP (Natural Language Processing), conversational AI gives businesses the power to stay on top of the game.

Why can we say that?

Today, digital-first marketing is a growing trend and conversation is the defining element of a digital-first customer experience.

Is your mind racing with questions like what is Conversational AI? How does it work? What are its benefits? Can my business benefit from Conversational AI?

Well, this article answers each of those questions. By the end of this article, you will understand all you need to know about conversational AI.  

What Is Conversational AI

Conversational AI is a subset of Artificial Intelligence. It uses Machine Learning (ML), Natural Language Processing (NLP), neural networks, and speech recognition technologies to mimic human conversation. Conversational AI can empower businesses to automate highly personalized customer service resolutions at scale. This makes the customer’s experience unique and relevant while reducing the effort and resolution time of the company. As a result, you have happy customers who stay loyal to your brand. 

Conversational AI is becoming one of the most popular technologies. The global conversational AI market size is expected to grow at a CAGR (Compound Annual Growth Rate) of 21.8% by 2026.

This unique technology is used to engage customers in services such as support, marketing, helping a prospect enter a funnel, and even sales. Conversational AI will make brands more human and help engage with customers more personally. 

The most common use of conversation AI experience is through voice assistants. This allows brands to participate in direct and uninterrupted conversations at scale.

Read more: Capitalizing on AI Chatbots Will Redefine Your Business: Here’s How!

How Does It Work?  

As mentioned earlier, NLP is one component that enables conversational AI. It is an umbrella term that includes NLU (Natural Language Understanding) and NLG (Natural Language Generation).

Human language is complex. People can say the same thing in many different ways. However, a computer can decipher customers’ intent with the help of natural language understanding technology. It looks at the context of what a customer said to accurately understand what a person needs. Leveraging NLU can enable conversational AI to understand grammatical mistakes, abbreviations, slang, and misspellings just like a human would.

Once it understands what a customer wants, ML is used to determine the appropriate response. Over time, conversational AI learns which response is the best and improves its accuracy. 

Finally, NLG creates an easy-to-understand reply that’s as human-like as possible. Advanced conversational AI can use contextual awareness to remember bits of information to facilitate more natural conversation. 

How Does Conversational AI Benefit Different Industries?

Conversational AI technology has substantial benefits for businesses across industries. Here are the most important benefits:

1. More engaging and easy interactions

Reading dry FAQs can be boring and may drive your potential customers to your competition.  On the other hand, having the choice to take part in a conversation can be more engaging and has the potential to convert your leads. 

Because conversational AI can use past interaction history or other relevant data, it can personalize each customer interaction. It spares the customer the trouble of searching through multiple pages to find answers to his questions.

2. Higher customer satisfaction

Conversational AI allows industries such as healthcare and hospitality to provide real-time information to their end-users. AI-powered chatbots can be accessed more readily than live support. Such quick support helps avoid long waiting times improving customer experience. Improved customer satisfaction can impact customer loyalty and referrals. 

Read more: 5 Leading Chatbot Use Cases Explained with Real-life Examples

3. Greater support with minimum cost

Customer care costs have a high impact benefit on finance industries. Conversational AI can help keep customer care expenditures in check. It can improve overall efficiency and productivity by handling routine issues much faster. These bots can also reduce customer support tickets.

They can deflect the number of routine tickets sent to human agents and boost team productivity. Chatbot templates can be used to collect information and help resolve clients’ queries faster. AI-powered bots provide relevant information faster and boost the accuracy rate over time. They can learn from past interactions and continuously evolve. 

4. Improved lead generation

Lead generation is the foremost goal of sales and marketing teams in industries such as insurance. Virtual assistants can engage visitors who browse the site and improve lead generation.

5. Increased operational and customer support efficiency

Conversational AI can come to the rescue when a business experiences a sudden rise in the volume of chats. Plus, these chatbots are cheaper and faster than hiring new agents. With automated operations, businesses can focus on other important functions. 

Additionally, conversational AI can determine a customer’s emotional needs and communication preferences from previous interactions. Hence, deploying a conversational chatbot is a wise decision during the holiday season.

6. Increased reach

Conversational AI enables your brand to reach a wider audience as it can understand both verbal and written speech. For example, you can reach elderly and hearing or vision impaired customers who find it difficult to navigate the web.

7. Boost revenue

Conversational AI can considerably reduce website costs.  When properly implemented, a conversational AI chatbot provides live support and assistance 24/7. They can qualify leads by asking predefined sales queries to nurture the lead.

Once the lead fills a form or signs up for a newsletter, the chatbot can analyze the text of the lead and find the most appropriate response. This is especially useful for banking services and increases their revenue. 

Conversational AI chatbots can quickly act on positive user intent and present a service or product that meets their preferences. 

Use Cases

1. eCommerce

Conversational AI helps businesses form customer relationships that last and ultimately sell more products. It can help in cross-selling and upselling products, finding specific products, and placing orders. It can also answer FAQs, make suggestions about the size, and even help with returns.

2. Banking

Conversational AI can be used to provide a simplified and intuitive customer experience. It can facilitate transactions, help with account services, and assist customers to apply for loans.

Among the best use cases of banking are helping find a nearby ATM, assisting with mobile deposits, and sending billing reminders and notifications. 

3. Insurance

Conversational AI can help distribute products, resolve claims, and increase customer awareness and education. It can also manage renewals, and gather customer feedback and reviews. 

4. Healthcare

In many ways, conversational AI can make things easier for patients, doctors, nurses, and other healthcare staff.

It can improve operational efficiency by answering common health questions, booking appointments, and checking up on patients. It can even escalate emergency cases.

Read more: MUSA: Fingent’s AI-powered Virtual Assistant Helps Employees With HR & DevOps Queries

Quick Resolutions, Seamless Conversations

Today, customers expect a quick resolution and seamless conversations when interacting with your business. Conversational AI will assuredly provide personalized assistants that both serve and predict customer needs. 

There is no doubt that conversational AI will continue to evolve into a sophisticated technology. Given that, your organization needs to clearly understand what conversational AI is so you can leverage it and build customer experience around it.

Give us a call, get your business set up with Conversational AI, and get set to reap the rewards.

Better businesses need better cyber security.
Regrettably, threats to cyber security have become the new norm across public and private sectors. The pandemic affected all types of businesses. If anything, uncertainties around remote working amplified cybercrime. As a result, cyber security’s importance has become more clear now than ever before.
As cyberattacks become more sophisticated, businesses will have to stay one step ahead. Security professionals need strong support from advanced technologies like Artificial Intelligence (AI) to protect their companies from cyber threats.
AI can enable security teams to handle greater and more complex threats than ever before. More specifically, it has proven to identify and prioritize threats. In some cases, AI has even taken automated action to quickly remediate security issues. This article considers how AI can redefine the cyber security needs of an organization.
Before we discuss further, let’s find out the impact cyberattacks can have on businesses.

How Cyberattacks Affect a Company’s Performance and Value 

Protecting a company against cyber threats is costly. It can impact the relationship between your company and your customers.
Unfortunately, cyber threats are never static. Millions are created each year and are becoming more and more potent.
In a survey conducted by Hiscox-Cyber Readiness Report, 28% of the businesses that suffered attacks were targeted on more than five occasions in 2020. Companies have lost millions to such cyber security breaches. Companies like financial services, technology, and energy were hit the hardest.
That is not all. Cyber security breaches have caused several other damages including:

• Outlays such as insurance premiums and public relations support.
• Operational disruption.
• Altered business practices.
• Business’s standing and customer trust.
• Stolen intellectual property including product designs, technologies, and go-to-market strategies.
• Legal consequences.

Read more: Quantum Vs Neuromorphic Computing – What Will the Future of AI Look Like!

How AI Contributes to Cyber Security 

Cyber threats are real and certainly worrisome to businesses. It is important to protect critical digital assets.
However, it takes planning and commitment of resources. With good security operations, you can stay on top of most of the most serious cyber threats. True, there may be smart thieves, but Artificial Intelligence can provide smarter security.
Here are 5 specific ways AI can contribute to cyber security:

1. Robust Zero-Day Malware Detection

Malware is unpredictable. And signature-based tools will not detect attacks that have never occurred before. Given that, is it possible to defend against something unpredictable? Yes!
AI is cable of grasping all the possibilities and finding relationships that traditional security tools would miss. While traditional security strategies have their place in cyber security, they are insufficient to detect and prevent zero-day attacks.
Zero-day attacks are best detected by automatically identifying aberrant behavior and alerting administrators immediately. AI can enable organizations to be more proactive and predictive with their security strategies.
Artificial Intelligence provides visibility and security for an organization’s entire data flow. AI helps organizations gain such visibility by dismantling each incoming file to search for any malicious elements. Simultaneously, it also looks at the user and network behavior and anomalies from expected activities.
Together with ML, AI adapts its behavior to new network conditions, constantly adapting to evolving security conditions. Even those hackers who use modern ML penetration methods cannot be fool AI-enabled cyber security.
We cannot stop security breaches from happening. But Artificial Intelligence helps organizations avoid potential disruptions before attackers wreak havoc.

2. AI Can Safeguard Large Amounts of Data

Whether a company is small or mid-sized, there is a lot of data exchanged between customers and the company every day. This information must be safeguarded from potential cyber threats. Cyber security experts cannot always inspect all the data for potential threats.
AI is the best option to detect threats to routine activities. Because of its automated nature, AI can sift through large amounts of data in real-time and identify any hazards lurking amid the chaos.
Read more: Artificial Intelligence and Machine Learning – The Cyber Security Heroes Of FinTech!

3. AI Takes Care of Redundant Cyber Security Operations

Hackers constantly modify their methods but the fundamental security practices do not change. Plus, they may weary your cyber security worker.
Artificial Intelligence takes care of redundant cyber security operations while imitating the best of human traits. It also does a thorough analysis of the network to locate security flaws that may harm your network.

4. AI can boost response time 

Ideal security is the one that can detect security threats in real-time. The principle of ‘a stitch in time saves nine’ applies here.
Integrating AI with cyber security measures is a sure way to detect and respond to attacks immediately. Unlike humans, AI does not miss a spot when examining your system for risks. Besides, it can detect risks early, thereby boosting response time.

5. Authenticity Protection

Most websites allow users to log in and access services or make purchases. You will need greater protection as such a site contains private information and sensitive material. To maintain customer trust, it is important to ensure all data about your guests remains safe while accessing your site.
Artificial Intelligence can provide an enhanced security layer. AI can secure authentication when a user wishes to connect their account. Login measures like CAPTCHA, fingerprint, and facial recognition are used to determine if the attempt is legitimate or not.
Read more: Safeguarding IT Infrastructure from Cyber Attacks – Best  Practices

Do Not Be Afraid!

Fingent is your reliable security partner. We provide professional security with reliable service. As a proactive security partner, we look ahead to ensure your business is successful far into the future.
Using AI’s real-time monitoring capabilities, we can spot potential issues before they become a major problem. Security experts Fingent are aware that cyber security threats are not limited to work hours. Our professionals here at Fingent will be there for your business whenever you need us.
We are in business today because of the reputation we built with our customers. We offer a unique level of enterprise IT support, and our clients can rest easy knowing that their business is always protected.
Give us a call and let’s discuss your security needs.