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.

Read more: Custom AI Copilots: Unleashing New Opportunities

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.

Read more: AI Recruitment: The New Norm In Hiring & Recruiting Industry

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 ai 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.

Read more: AI Implementation For Businesses

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. 

Cyberattacks are hitting the headlines with increasing frequency. Data breaches and attacks are currently inevitable parts of running an organization. Cybercriminals are adept at using phishing, malware, or insider threats to infiltrate infrastructure and steal confidential information.

Businesses that compromise their cybersecurity face more than just the loss of confidential data. Cybersecurity breaches can affect a business’s market value, jeopardize the brand reputation and compromise competitiveness. The effects of a single cyber-attack can be permanent and devastating.

How do you combat this era of over-smart cyber criminals? You need more than cyber security. What you need is cyber resilience!

Are you wondering what the best way to protect your company from within and without is? Do you want to secure your business in this volatile economic atmosphere?

If YES is your answer, please continue reading to find out why shifting from cybersecurity to cyber resilience is necessary.

Why Has It Become Necessary to Shift from Cybersecurity to Cyber Resilience 

Pandemics are not the only calamities from which a business needs to build resiliency. Any unforeseen event, be it a natural calamity, a shift in the economy, or anything else, needs to be part of comprehensive disaster recovery planning.

Such unforeseen events provide many risk-based opportunities to pivot in response to risk. Chief among these is digital transformation. Here are four risk-based opportunities that make it necessary to shift from cybersecurity to cyber resilience.

1. Strategic risks: Included among many others are business continuity, reputational hazard, competition, insurance legal risks, and more. If these risks are not mitigated in time, they can affect organizational sustainability.

2. Financial risks: Financial risks have implications for regulators, tax complexities, and employee outsourcing.

3. Operational risks: Operational risks include organizational and digital functions, from employee well-being to AI and robotics. It can affect the business process and all those involved.

4. Remote work: This can easily expose an organization to cyber threats.

If an organization becomes a target of persistent cyber threats, its networks will likely be compromised. That is why businesses must be ready.

Cyber resilience allows an organization to minimize the impact of persistent threats. It lowers the probability of a successful attack and minimizes the damage if the attack is successful.

Read more: A Detailed Whitepaper On – Is Cyber Resilience Over Taking Cybersecurity for Good?

How Are They Different From Each Other?

1. Cyber security-the mighty wall

Cyber security is about reacting to a cyber-attack while cyber resilience is about anticipating a possible attack.

Cyber security is about technologies and processes designed to shield computer systems, networks, and data from cyber threats.

For example, when an empire wants to prevent security breaches, it might first build a huge, robust wall. If it feels that is not sufficient, it may construct another wall that is higher than the existing wall and perhaps add a ditch.

Can such measures completely protect an empire from a breach? Well, history has a different story to tell.

Cyber security is somewhat like that wall. It is more focused on preventing hackers from breaching ITs’ security wall. While it may prevent the majority of attacks, a hacker can still find ways to breach that mighty wall when the landscape changes. Despite all measures, an organization may be still vulnerable to a cyber-attack.

Read more: Artificial Intelligence and Machine Learning: The Cyber Security Heroes of FinTech!

2. Cyber resilience-an ever-equipped and ever-prepared tech-ninja

The goal of cyber resilience is to anticipate, withstand, and adapt. It depends on the theory of “when there is a cyber-attack,” not “if there is a cyber-attack.”

A cyber resilient business is like a ninja, able to respond and recover from a cyber-attack. Such a business can continue to operate through the attack, and eventually, get back on track and become more capable of withstanding future disruptions.

It helps organizations to foresee hackers’ activities and be informed about the possible threats they pose. This way organizations are prepared to prevent and protect, defend and respond successfully to any attacks.

Cyber resilience is not just a security measure. It is a cultural shift – a full-time task that applies security best practices to defend an organization’s networks and systems. here are five key areas:

• Prepare: Preparation is key to success! Hence, to prevent cyber-attacks an organization requires a multi-layered approach. This includes technology, people, and processes. Cyber resilience involves having comprehensive security policies and providing training and in-work support to ensure that all involved know their role.
• Protect: In addition to basic security software, more sophisticated solutions like endpoint detection and response solution provide a greater degree of protection. Security awareness training and data protection layers offer even greater cyber resilience levels.
• Durability: Building durability into an organization is one of the end goals of cyber resilience. Adopting a single platform for data and content can make it easier to protect an organization as a breach can be identified quickly and quarantined before it affects other sections. All this while, employees can continue to access other systems and data.
• Recovery: Resilience means rising every time we fall. Cyber resilience means returning to normal no matter what. To avoid a complete halt to all business operations, an effective data backup and recovery is essential. Automated, granular backup and recovery of data to a separate network will enable businesses to quickly restore data that may have been seized or wiped.
• Adapt: According to a writer, adaptability is the simple secret of survival! And that is a key component of cyber resilience. Security solutions that leverage up-to-the-minute threat intelligence ensures that a network can adapt automatically to the latest threats. This sort of intelligence allows you to understand the current threats and make accurate predictions about likely attacks in the future.

Read more: Redefining Cyber Security Needs With AI!

ACT and not REACT

Data and infrastructural security are the topmost concern of every organization. Active and continuous protection is a must for tools and techniques. This is also why investing in cyber resilience can never go wrong in any condition.

Cyber resilience equips businesses with technical know-how in order to prepare for the worst and ensures it can deliver in the worst situations.

Cyber resilience involves a change of mindset. It is also about security operating within the organization and beyond. It is only by thinking of overall network resiliency that businesses can surmount existing threats, and overcome future threats.

Security experts at Fingent have their finger on the pulse of the digital world and know how to nip cyber threats in the bud and keep your business resilient from attacks. This means that you leave your cyber worries in our hands with the confidence that it will be dealt with effectively.

Call us and let’s discuss your security needs and how we can fulfill them. 

Customer expectations are changing dramatically. In response, digital transformation is becoming an unstoppable wave that is overtaking all sizes of businesses. To succeed in this environment, it is vital that businesses transform into smart and intelligent ecosystems.

Digital transformation is continuously increasing its presence, by developing ecosystems that are increasingly adaptive and provide sustainability. Companies are developing a dynamic network of external partners and internal departments to provide seamless customer service.

While developing an intelligent ecosystem has been a red-hot subject during the pandemic, it is likely to further accelerate adoption, especially among mid-sized businesses. Given its value generation and potential to grow and generate revenues from new products and services, most mid-sized companies are actively considering transforming their ecosystem business model. 

Is yours a mid-sized business?

Are you among the many who are wondering how to remain sustainable in today’s fast-evolving market?

If so, then this blog is designed to help you understand the reasons why you need an ecosystem that can create value. 

Embrace The Future with A Smart Ecosystem

We live in a digital world, so moving with intelligent ecosystems is key to the continued improvement and growth of your business. The future of your business depends on the ability to do more with less, speedy services, and the elimination of inconsistencies. 

It is time for mid-sized businesses to move into the digital age and finally put their existing tech stack to work through the digital ecosystem.

Here are five reasons why mid-size businesses must reshape ecosystems:

1. Logistics will continue to grow in complexity

Technology is changing as the world continues to change. Given that, the many needs and demands of customers and partners are changing. Those changes will continue to grow in complexity as new suppliers and businesses arise on the world scene.

To keep pace with these changes the ecosystem must adapt, creating a continuous evolution cycle. A Digital supply ecosystem powered by Artificial Intelligence can help future-proof operations. 

2. Ability to make informed decisions

Today’s technology provides many things at your fingertips. Customers today, thus expect quick responses, real-time updates, and services at their doorsteps and fingertips! When demands increase, companies need to be efficient and capable of making quick decisions. 

Besides, making decisions regarding delivery time, costs, and outcomes based on partial information can be detrimental to the growth of your business. On the other hand, digital ecosystems allow you to access real-time data whenever and wherever you need it, enabling you to make informed decisions that impact your business. 

3. Bridge and divide for better control

An ecosystem bridges a network of organizations, people, information, and resources to move a service to the customer. 

Empowered by AI, the digital ecosystem has enabled businesses to move to a more streamlined and successful chain of command. It helps bridge every team member and trading partner making quick and easy communication possible. This can be done on each and every level, without exceptions. 

Read more: A Detailed Guide to Understanding Digital Business Transformation

4. Fast and free is the in-thing 

In the instant world, customers expect fast and free delivery and every shipper strives to provide this. Customers would like to track their items digitally and receive real-time updates. 

The current gold standard of delivery experience is two-day, one-day, or same-day deliveries. It is the minimum requirement for supply ecosystems to provide such deliveries to stay ahead of the game.

5. Recapture sustainability

Providing fast and unique customer experiences requires more energy and resources. It affects the bottom line of the business and can cause you to cut corners in other areas to make up for the expense. Doing so can have a detrimental effect on sustainability.

This is why businesses must look for ways to recapture sustainability without compromising on the gold customer experience. And leveraging a digital ecosystem that is powered by emerging technologies is one means to that end. 

6. Internal and external collaboration

The strategic partnership between large organizations and large platforms is increasing. Fortunately, the ecosystem allows partners to share data when required, scale assets up or down as needed, and collaborate internally and externally. 

Additionally, enormous amounts of cross-functional data with AI help pinpoint the root causes of issues and identify opportunities for performance improvement. 

Read more: It’s Time To Pivot Your Legacy Software To A Platform Ecosystem!

Reshape Your Business Ecosystem with Fingent!

Creating a smart ecosystem from scratch would open up a whole new world of possibilities for your business. However, the first step would be to get your transformation right. 

George Westerman a research scientist aptly said, “When digital transformation is done right, it’s like a caterpillar turning into a butterfly, but when done wrong, all you have is a really fast caterpillar.”

Fingent doesn’t just help you deploy technologies! We help you digitally transform into a future-proof and successful organization. 

How do we do that?

Here’s how we helped one of our clients transform with a customized smart ecosystem!

The client: Cheetah Transportation System – a leading truck transportation service that provides transportation of time-critical freight throughout the United States.

Their requirement: They needed to rethink their existing business processes to build a sustainable competitive advantage.

Their challenges:

• Complexities in placing and handling orders
• Licensed third-party software was partially used but was increasing overhead costs
• Ineffective Master Data Management
• Inability to provide their customers with real-time updates about their shipment
• Complex off-the-shelf systems
• An inefficient process led to delays, increased trip cycles, and wasted resources and time

What role did Fingent play in its digital transformation?

After a thorough analysis of their major pain points, Fingent helped Cheetah Transportation System build a customized software solution that included a web app for dispatches and administrators and a mobile app for drivers to simplify their interactions with the company. Their new transformed ecosystem streamlined:

• Rate Sheet Management
• Master Data Management
• Invoice & Accounting
• Payment Processing
• EDI and GP Integrations
• Dashboards and Reports

The solution’s overall architecture helped Cheetah maintain business transparency, avoid potential disruptions and do much more than what was possible with their previous system. They could reduce the time taken to respond to customer queries by 30%, and save overall time by 40% with automated tasks and real-time reporting. The company also gained an increased capability to ensure continuous performance optimization.

At Fingent the digital transformation strategies are focused on the value it brings to businesses and their customers. Once we identify gaps and growth points, we offer customized technology solutions that can help clients to stay ahead of their competition in the current fast-changing digital world.

To know more about how we can help you reshape your business ecosystem for a sustainable and successful future, connect with our experts today!

Augmented Intelligence has presented enormous potential in several sectors. Enterprises are adopting Augmented Intelligence to gain the best outcomes. 

After 2 years of disruption, partners, employees, and customers increasingly expect businesses to focus on long-term value creation. With this new mandate, enterprises adopted Augmented Intelligence to build resilient businesses that prioritize communities, employees, and better customer experience.

Augmented Intelligence is poised to improve the speed and quality of employees. It improves household and workplace security, combats fraud, and increases productivity. Deploying Augmented Intelligence correctly can diminish information overload and lead to fast, data-driven decisions. 

This blog discusses how you can improve business performance with Augmented Intelligence.

Some confuse Augmented Intelligence with Artificial Intelligence (AI). Is there a difference? Let us first find that out. 

What Is Augmented Intelligence?

Essentially, Augmented Intelligence boosts human abilities and has the potential to revolutionize how we live and work. Augmented Intelligence is the utilization of AI and other types of automation to provide new and better information to help professionals make better-informed decisions, rather than having fully automated decisions. Augmented Intelligence may also eliminate rote tasks, freeing people to reflect and evaluate more easily.

AI enables machines to think and act like humans, whereas Augmented Intelligence uses the same machines to assist humans with specific tasks enabling them to make smarter and faster decisions. That means not only discovering hard-to-see trends, conditions, and outliers but also presenting these things to decision-makers in timely and easy-to-understand formats.

Read more: The Convergence of Edge Computing and AI: Why Is It Important For Your Business?

Does Your Business Need Augmented Intelligence?

Augmented Intelligence can make sense in any business where experienced and knowledgeable employees are key to business success. Job functions that involve making sense of many factors can benefit from Augmented Intelligence capabilities that organize or synthesize information. Companies that have difficulty finding people with the right experience or with business roles that involve lots of training can employ Augmented Intelligence to reduce training needs.

1. Distribute accurate information companywide

Deploying Augmented Intelligence helps data scientists prepare data, gain the latest insights, and distribute necessary information to all involved. It offers the full benefits of connecting technology and analytics with your employees. 

2. Ease of use

The Augmented Intelligence capabilities help routinely assemble information from all types of structured data, from multiple sources. After gathering it, it can clearly present relevant data for humans to see from every angle. This allows employees to be more informed on news across their organization.

How Does Augmented Intelligence Improve Business Performance?

Augmented Intelligence is a partnership model of people and AI working to enhance decision making, cognitive performance, and more. Business leaders striving for competitive advantages are finding that Augmented Intelligence elevates the prowess of their workforce in a variety of areas. Here are some ways Augmented Intelligence can improve business performance.

1. Build a “high-trust network”

New employees may not be familiar with how the business functions. Such unfamiliarity can shift your work culture to higher supervision leading to more towards a “low-trust network.” 

Leveraging Augmented Intelligence can equip newer staff to rapidly achieve the competence they need to take responsibility for running their own areas of business leading to a “high-trust network.” 

2. Prevent blind spots

Businesses that cannot see the necessary information when they need it grows slowly. 

Augmented Intelligence can help you see all the information about your business, customers, employees, or even competitors. Such information will help plan your business strategies meticulously, yet quickly.

3. Improve the customer environment for better satisfaction 

Augmented Intelligence helps businesses create innovative products and services. These innovations can enable a business to address customers’ queries faster, improving the customer environment. 

Read more: Memorable Customer Experience – A Key For Brand Transformation!

4. Faster and smarter decision making 

Businesses that make decisions faster and smarter are the ones that grow and remain resilient during a critical period. 

Using Augmented Intelligence to make suggestions to employees and record their responses can help you come up with the best solutions faster. It can help achieve faster results and save significant costs by reducing risky experiments.

5. Tighter security and lighter resource

Augmented Intelligence enhances the speed of knowledge in human resources and cybersecurity. By using the capabilities of Augmented Intelligence, companies can sense, decide, and act at speed and scale. Thus, companies can achieve faster results, cut costs, generate insights, and improve security. 

6. Enables strategic planning

Businesses without strategic planning are like a traveler without a map. Strategic planning creates a map for businesses to follow and correct course when needed. This is where Augmented Intelligence plays a key role.

Augmented Intelligence tools can help clean data sets and forecast future trends based on social trends and customer feedback. Thus, you will be able to make smarter marketing plans, faster.

7. Enhanced customer relationships

The success of a business greatly depends on customer relationship management. The better the relationship, the easier it is to generate leads and revenue. 

Challenge is when the business grows, the customer base increases. Such an increase can affect how you manage your customer relationship leading to either satisfied or dissatisfied customers. Thankfully, you can manage customer relationships in a sustainable and consistent way with Augmented Intelligence.

8. Keep tabs on financials

Financial monitoring is continually evolving. It’s no longer enough for companies to have regular, reliable financial reports. Today’s businesses benefit from real-time notifications and early warnings of trouble. Examples of not being able to monitor financials effectively could be the inability to invoice fast enough, detection of inaccurate billing, or identification of services that are no longer profitable. 

Augmented Intelligence capabilities can help businesses keep track of their financials even during a period of intense growth. 

Read more: Can Augmented Intelligence Improve Finance and Accounting?

Let Fingent Create a Recipe for Success with Augmented Intelligence

If Augmented Intelligence is like fine dining. Artificial Intelligence, RPA, and Machine Learning are just some of its ingredients. An experienced chef like Fingent can combine them in the right ways and at the right time to make an outstanding dish. 

Fingent professionals are experts in applied technology. We work with clients to understand their business objectives. By employing the right mix of technology we devise options for advancing their business strategy within available budgets and required timeframes.

With an ever-evolving competitive landscape, enterprises deploying Augmented Intelligence will be quicker to insights, faster to market, and more able to leverage data to navigate changing conditions today and into the future. Our experience working with many clients from many sectors and types has equipped us with insights beyond a narrow and vertical. 

 Give us a call and let’s discuss your project.

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. 

Read more: Legacy Software Modernization: For Organizational Survival!

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 top software development company, 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!