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!   

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.  

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 the cloud ML engine on the 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 custom software development experts 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. 

If you’re a business with an expanding online retail footprint, your hard work actually begins once a customer places an order. Each new order triggers a multifarious chain reaction, right from confirming the order through payment acceptance to picking, packing, and finally shipping the consignment to the right location. As digital shopping becomes the primary buying method today, it’s important for brands to simplify online ordering for their customers.

How can you make your order processing and fulfillment smooth enough for both your customers and employees? 

If you’re a small business, you might be able to handle your orders with basic pre-packaged software. But as your business grows, you need a customized order management system to fulfill the orders gushing in. With a custom order processing software, your business can bring the best of both worlds, that is, streamline your order processing and fulfillment and simplify order placement for your customers.   

View Infographic: Custom Software vs. Commercial Off-the-shelf Solutions

What is an Order Management Software?

Order management refers to the set of processes used by an organization to track, manage, and fulfill an order, right from the time when it (order) is placed by a customer to when it is safely delivered at the right destination. 

Order management systems are software tools used to monitor the end-to-end customer order journey. With order management software, you can organize and automate processes, keep track of your merchandise, control the delivery process, and ensure that your customer receives the right order at the right time in a good condition. 

Say you’re running an online medical procurement store. A clinic places an order with you for disposable saliva ejectors. Your order management software checks if the payment was successful, send the order details to your warehouse, tracks the order form when it is being picked, packed, and shipped, and finally ensures that the saliva ejectors were delivered properly. 

Modern order management systems are capable of going beyond delivery and order fulfillment. They can record customer service actions, track returns or exchanges, prevent shipping errors and processing delays, and save profits by reducing refunds and reshipping costs. By collecting vital metrics that define your success and efficiency, your business can identify what’s working and what needs to be improved.  

Why Do You Need a Customized Order Processing Software?

Investing in an off-the-shelf order processing system is enough if you’re content with your business’s status quo. But it wouldn’t suffice if you’re thinking of expanding your business. Offering personalization is the only way to make yourself stand out from the competition and attract more customers. That means, making some serious changes to your existing workflow. When you try to alter your current workflow to incorporate personalization, your canned software offers limited ways to do it successfully. This is where a custom software solution comes to your rescue. 

Watch Video: Why Your Business Requires Custom Software

Custom order management software allows you to configure the workflows required to meet your specific business needs. If off-the-shelf software provides you with 80% of the functionality, custom software allows you to tailor the remaining 20% (or even more) to enhance your workflows and make your business future-proof. 

Some Inspiring Stories 

We’ve done it in the past and we’re doing it now as well! 

We’ve simplified what was once considered complex order processing, with custom-built ordering software that lets customers place orders quickly and allows businesses to track every order with improved efficiency and sophistication. Here’re a few inspiring stories.

1. Cheetah Transportation Systems

Texas-based Cheetah Transportation Systems leveraged Fingent’s custom software development services to implement a personalized transportation management system. The new system allows Cheetah’s customers to view their order status in real-time and access up-to-date shipping data. With a customized software solution, Cheetah re-imagined their logistics and supply chain operations:

• Streamlined and accelerated ordering, tracking, and delivery processes
• Cut licensing and subscription costs by eliminating complex third-party software integrations
• 30% improvement in Turn Around Time (TAT)
• 40% time-saving attained through automated tasks and real-time reporting 

2. AEC Advisors

Another pretty interesting digital transformation story is that of AEC Advisors. The New York-based investment banking and corporate finance advisory firm experienced a business transformation with a customized survey management cum analytics and reporting software developed by Fingent.  

• Ability to create and circulate customized surveys prior to the yearly conference held by AEC Advisors
• Quickly generate KPI reports based on survey responses
• Secure, scalable, and flexible IT architecture to address AEC’s specific needs
• Make it convenient for AEC’s clients to securely share complex financial information

3. Lakeside Cabins

A custom order management application for a manufacturer who builds customized sheds for growing families needing more space! That’s the story of Lakeside Cabins, headquartered in Ohio. The manufacturer wanted us to build an in-house software customized to support the different stages of their building processes. Fingent created a personalized, flexible, easy-to-maintain, and scalable order management software with the following features:

• Custom-built 3D configurator that allows customers to configure building designs, generate floor plans and invoices, and reduce human errors
• Integrated modules to manage CRM, dealers, orders, purchase orders, work orders, and route-optimized delivery schedules

Interested to explore similar success stories? Click here to read our top case studies. 

Business Benefits of Custom Order Management Software

1. Features that fit your business needs

A customized order management software offers the best features your business would actually require. Collaborate with the right software development partner to identify your unique business needs. Avoiding unwanted features helps you get cost-effective custom software within a shorter development cycle. 

2. Flexibility 

Your customers may want to split orders and deliver them to multiple addresses. Using an off-the-shelf software to split your shipments will increase your fulfillment costs due to longer development cycles. A customized order processing software offers the flexibility to split consignments, choose multiple payment modes for a single order, and a horde of other capabilities that will enable you to deliver an Amazon-like experience to your customers. 

Read more: Custom software solutions – the ideal way to build business apps

3. Easy to integrate with other tools

Most off-the-shelf software don’t offer flexibility in integration, making you spend more on missing software integrations. In contrast, custom order processing software offers makes it easy to integrate with necessary third-party ware that can improve the accuracy of your order fulfillment process. Fingent develops powerful APIs and plugins that support seamless integration of third-party tools with your custom software.  

4. Automation of mundane tasks

When your custom order management software does the heavy-lifting by automating invoicing, billing, banking integration, payment, and stock management, you can focus on improving your customer service. Automating mind-numbing operations will allow you to keep your order processing tasks much more organized and easier. 

5. Flexible pricing

Most pre-packaged order management solutions offer functionalities that your business doesn’t require and demand you to pay extra for useful features. A custom software solution is designed and developed after defining your objectives clearly. So you end up paying only for the features you use.   

Read more: Know What’s Driving Custom Software Development Costs in 2022

Develop Your Custom Software Application with Fingent

When you’re in complete control of your order management system, you will attain better visibility, productivity, and cost control. Custom software befits businesses of any size- small or large, as it can save your costs and support your long-term growth plans. Whether your requirement is to develop a custom inventory/ order/ warehouse/ transportation management software, our developers have considerable experience in handling anything that comes our way.

Read more: How to Choose the Right Custom Software Development Firm

Our core experience in developing B2B e-commerce applications, customized product ordering systems, tailored self-service payment portals, and an array of bespoke software solutions makes us a trusted software development partner to hundreds of organizations worldwide, including Fortune 500 companies.

If you want to learn more about custom software or would like to know how it can improve your bottom line, get in touch with us.     

Every small business requires an array of software to run its operations smoothly and successfully. When starting a new business, it may seem like your off-the-shelf software would suffice all your needs. As your business grows, your business management software should scale to meet your team’s evolving needs, boost the efficiency of your workflows, and be flexible to support new use cases. Custom software or a software application tailor-made to address your specific business requirements helps improve your market competency and realize ROI at a faster pace. 

How will you determine if custom software is the right fit for your small business?

Read on this post to learn more about custom software for small businesses. 

Read more: 5 Reasons Why Custom Software is Important for Your Business

Top Signs Indicating Why Your Small Business Needs Custom Software          

The classic “build vs. buy” decision is a pertinent question that every small business faces when addressing their software needs. Considering the cost, time, energy, and resources dedicated to custom software development, many SMEs adopt packaged software in a haste. Look out for these warning signs before deciding whether to build or buy. 

1. Employee Discontent

Find out if your employees are satisfied with your existing off-the-shelf software. Do they still stick to old-school tricks or find manual methods faster and more convenient? Are your employees forced to discover alternative workarounds to use the software? Do they still rely on spreadsheets and how-to guides for using the software? All these signs indicate that your off-the-shelf software lacks employee approval and can fail your business eventually.

2. Existing Tech Isn’t User-friendly

Rolling out enterprise-wide canned software that commands an advanced level of technical expertise will inflict more harm. It will complicate the processes for your employees and incur heavy training costs. Complex shelf software will fail the very purpose of technological innovation, that is, to simplify human efforts. If only less than 20% of your employees find the software workable, it’s better to build a customized solution.

View Infographic: Custom Software vs. Commercial Off-the-shelf Solutions

3. Wasting Time on Mundane Tasks

Is your software forcing your employees to spend their valuable time on routine activities that don’t require human thought and creativity? If your software isn’t allowing you to leverage the potential of automation, it can minimize your employees’ productivity and workplace efficiency. Automation of mundane tasks with minimal or adequate supervision is a must for small business growth and success.

4. Software Spend Drains Your Wallet     

Adapting a rigid off-the-shelf solution for your small business needs requires you to subscribe to third-party apps and pay multiple licensing fees. Most biz owners end up paying full price for unwanted features. Some companies would want to integrate estranged business applications to increase the usability of their shelf software. All these challenges lead to increased software spending.

5. Unable to Make Data-backed Decisions  

Your business data comes from multiple sources such as your website, emails, social profiles, chat, and conversation histories, helpdesk, and so on. How far is your canned software allowing you to make use of this data? Are your decisions driven by live data? If your dashboards aren’t getting updated in real-time and reports throw only past information, it’s time to consider custom software. Integrating multiple business systems and exporting all the useful data insights onto a centralized, user-friendly platform in real-time will empower small businesses to make rightful decisions.    

Watch Video: Why Your Business Requires Custom Software

How Can Your Small Business Benefit from Custom Software?

Small business competition has intensified in recent years. Thanks to the increasing democratization of digital innovation! Access to technological advancements is no longer limited to large enterprises. With a custom-built software, your small business can stay relevant and competitive.

1. Own Purpose-built Software 

Custom software development guarantees 100% alignment with specific business needs. You can rest assured that no crucial operations are left unsupported and there aren’t any wasted features. Share your unique requirements with a trusted custom software development company like Fingent and get exactly the features you would require on a long-term.

2. Uncompromised Security

Ready-to-use software is highly vulnerable to cyberattacks due to the widespread availability of code and proliferation of users. Owning custom code places your small business under lock and key and keeps your sensitive information hack-proof. Customized solutions offer built-in security with a specialized approach to development. Better compliance and data governance improves your organization’s reputation and trust. 

3. Improve Workflows and Efficiency

Attaining profitability amid stiff competition needs your employees to put in their best performance. Experienced custom software companies like Fingent can help you identify the workflows or business functions that can be improved with the right technology. This makes your business more efficient and maximizes the productivity of your employees.

4. Keep Costs Under Control 

Improved business efficiency transforms to lower operational costs. Technologies like automation enable your employees to complete more tasks in less time, without feeling monotonous. Custom software actually costs lesser than off-the-shelf solutions, considering the extra dollars you would spend on subscriptions, licenses, third-party integrations, software upgrades and maintenance, and other overheads required to make the shelf software workable.

Read more: Know What’s Driving Custom Software Development Costs in 2022

5. Round-the-clock Support 

Modern business might come to a standstill if technology stops working. A typical readymade software provider puts you into a long wait with back-to-back support tickets and repeated calls, whereas a dedicated custom software development partner offers access to a direct line of technical support to resolve your issues immediately.     

Read more: The Dos and Don’ts of Custom Software Development 

Tips to Choose the Right Software Development Partner

Hiring the services of an experienced custom software development agency will help you focus on developing a sustainable business model. How can you identify the right software development partner for your small business? Here’re a few tips we recommend:

• Identify your needs. Decide what you expect the software to do. List out your objectives. Use an application specification template to fill out your needs. This improves your communication with the software development vendor. It helps the vendor understand your expectations clearly. This can go a long way in finalizing the project’s scope. 
• Check the partner’s technical skills, expertise, and experience. Have they handled projects related to your domain? Read up their case studies and analyze their portfolios. Arrange catch-up sessions to learn more about their software development approaches and project management methodologies.  
• Ask for references. It helps you understand their reputation and trustworthiness. Use top B2B review platforms like Clutch and GoodFirms to evaluate their performance. Connect with the company’s past clients for more candid reviews. 
• Cost is as important as the experience and reputation of the software development partner. Bestow your project only if you’re confident of guaranteed ROI. 
• Is your development vendor passionate about your project? Figure it out over the initial meetings before the formal kick-off. Do they come up with unique ideas that improve your application’s value in the future? Make sure that their ideas are backed with convincing use cases or POCs.  
• Choosing a software development partner also depends on the quality of after-sales service and technical support. Do they provide cloud-based updates, software upgrades and maintenance, and other troubleshooting services when you need them? 

Selecting the right custom software development partner is a meticulous job. Check out our earlier post covering these and more crucial tips in detail. 

Also read: How to Choose the Right Custom Software Development Firm

Why Choose Fingent as Your Custom Software Development Partner?

Over the past two decades, Fingent has been serving as a reliable and capable tech partner for many leading global brands, including Fortune 500 companies. With an impeccable track record as a successful custom software development partner, we’ve helped improve cash flow and business efficiency for many clients. If hiring in-house developers is costing you a fortune, extend your development team with our dedicated talent pool at reasonable rates. 

Read more: Top Benefits of Outsourcing Software Development Services

We’re in track of the latest tech development trends and help our clients explore new and emerging tech such as Augmented Reality (AR), Virtual Reality (VR), Internet of Things (IoT), 3D Web Configurator, Robotic Process Automation (RPA), Artificial Intelligence (AI), and so on. If you’re an aspiring small biz owner trying to make the most of technology without burning a deep hole in your pocket, connect with our team and get started. Let’s help you build scalable and robust small business software.     

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. 

Conversational AI: Innovative Use Cases Transforming Industries

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 with Conversational AI

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.

Connect with Fingent software development experts, get your business set up with Conversational AI, and get set to reap the rewards.

Data is the very foundation of insurance operations. Until the introduction of modern data analytics technologies, insurers used to make decisions based on the insights garnered from historical data. The advent of cloud computing, the divergence of data sources, the instrumentation of datasets, and the availability of real-time data have fundamentally transformed the way insurance operates today. Modern insurance carriers seek innovative methods to visualize and contextualize data from both physical and digital assets. With digital twins, insurance leaders can make the most of data, assess their readiness to face disasters, prevent damages before they occur, and optimize core insurance operations. This post explores why digital twins are vital for insurance companies in the future.
Read more: Is Digital Twin Promising A New Era for Healthcare?

The Importance of Digital Twins in Insurance

Digital twins are computerized models or virtual replicas (simulations) of physical objects such as devices, assets, products, or processes. The biggest advantage of digital twins is that they operate in real-time, taking cues from updated data. This holds immense potential for the insurance industry, which heavily relies on data insights to make critical business decisions. Digital twins leverage connected technologies (IoT, sensors, real-time data monitoring systems) to help insurers define new policies or packages, mitigate risks, reduce administration costs, and enhance core insurance operations such as underwriting, claims processing, new policy creation, fraud detection, customer assets evaluation, etc. They also allow insurance companies to prevent unplanned downtimes and discover new growth opportunities.
These stats prove why digital twins are important for insurance companies going forward:

• Data Bridge Market Research estimates that by 2027, the global digital twin financial services and insurance market will account for USD 77,530.82.
• 87% of insurance executives agree that digital twins will strengthen their ability to collaborate in strategic partnership ecosystems, crucial for long-term success.
• 93% of insurance executives realize the necessity of a centralized and intelligent data hub that helps them understand the defects of their current processes and remodel their operations.

Digital twins can act as a virtual insurance lab for executives to predict and evaluate any risk scenario and make smart decisions. With digital twins, Insurance is moving to Assurance, a new business model that saves huge compensations from being paid off by averting losses before they occur. Let’s consider the example of a cargo vessel that is ferrying goods from one port to another. Telematics is alerting the vessel’s crew that the ship will soon be exposed to a sea storm. The vessel’s digital twin can collect data from the entire ship’s systems and assess how the storm will impact the vessel. This enables the captain to quickly turn their route and reach the safest port nearby. This is a classic example of how digital twins help upgrade insurance into assurance.

Digital Twins Can Improve Core Insurance Operations

Digital twins transform five core areas of insurance operations:

1. Underwriting

Underwriting refers to the process of pricing risks based on risk assessment. With real-time streaming of data and virtual simulations, underwriters can gain a better understanding of pricing risks based on different scenarios. Digital twins allow insurers to analyze more heterogeneous datasets within a short span of time, such as cases of heart attacks, house fires, vehicle mishaps, earthquakes, floods, and other catastrophic incidents that don’t occur frequently. This enables underwriters to fix more competitive premiums. Commercial line insurers can leverage digital twins to process workers’ compensation claims more effectively, reduce premium audits, and customize premiums to match the changing workforce.

2. Distribution

By creating virtual replicas of customer habits, insured assets, and external events affecting customers’ assets and decisions, insurers can gain a more comprehensive view of the volatile market. Digital twins can simulate consumer behavior patterns based on their online activities, shopping data, and search habits. This allows insurance executives to understand customer journeys and practice context-relevant selling across the omnichannel spectrum. Insurers can also push one-click purchases across different customer touchpoints to boost distribution. The more you know about the customer, the better you can provide personalization. With online simulations and near-real visualizations, insurers can improve cross-selling and upselling.

3. Claims Processing

Digital twins help fast-track claims processing by reproducing the scenarios or circumstances behind the appeals, such as conditions of damage, car accidents, fire breakouts, etc. Claim adjusters can leverage digital twins to simulate accidents and assess their impact on the claimant’s property or other valuable possessions. This avoids the need for expert examination and helps precisely determine the insurance company’s liability. To prevent unwanted delays in claims processing, executives can compare the virtual and physical records of an accident or a house fire. Thus, digital twins in claims processing allow insurers to respond quickly to their customers.

4. Back-office Administration

Like HR, Finance, Procurement, Inventory, and other corporate functions that can be augmented with automation, several back-office operations in insurance companies can be improved using digital twins. It’s possible to create the virtual simulation of a blockchain-based smart contract prior to implementing the actual contract. Insurance carriers, customers, claim adjusters, and relevant policy stakeholders can explore how the smart contract would work in real-life and ascertain how secure the contract would be. While blockchain ensures transparency and trusted execution of smart contracts, digital twin stores and evaluates the insurance data in real-time. This helps avoid any legal disputes and complications in the future.
Read more: How Blockchain enables the insurance industry to tackle challenges

5. Fraud Detection  

FBI reports that in the United States, the total cost of non-health insurance fraud alone accounts for USD 40 billion per year. The rising insurance fraud costs force carriers to increase their premiums, which has a direct bearing on many American families who will have to pay higher premiums every year. Thanks to digital twins, it’s now possible to reproduce an event that resulted in a catastrophe or damage. Claim adjusters can determine the claim’s accuracy by comparing the applicant’s data with the simulated version of the incident. As a result, inconsistent claims can be detected quickly to reduce the carrier’s liability and save costs.

Leading Insurers Are Experimenting with Digital Twins

Leading reinsurer Swiss Re has partnered with Microsoft to establish a Digital Market Center for building “risk digital twins” – a virtual world that leverages AI and big data to create simulations expounding different risk scenarios. Swiss Re uses this knowledge to forecast supply chain risks, disasters, and other financial exposes. It allows insurers, business owners, and end consumers to make cost-effective and timely interventions.
Read more: Transforming Insurance with AI

Piprate, an Irish Insurtech startup joined the Digital Twin Consortium in 2020 to promote the potential of digital twin technology in the insurance industry. Piprate builds digital twins of insurance risks to solve the industry’s predicaments related to vital financial data acquisition and data sharing.
AI Journal reports that the insurers who participated in their pilot study titled “Digital Twins of Risk AI” (a UK grant-funded project) were able to gain a 360-degree view of risk in real-time across 100% of their portfolios.

Looking Ahead!

To face the disruption and navigate the uncertainty triggered by the COVID-19 pandemic, insurers need to evolve from self-contained businesses to strategic players in a partnership ecosystem. Besides streamlining data from discrete devices, digital twins offer a valuable source of intelligence for insurers. Following the unpredictable times ahead, insurance leaders will have to rethink their long-term plans and gain the ability to amend packages and make interventions in real-time. Fingent top custom software development company enables insurance leaders to prepare for a more agile and intelligent future by leveraging digital twins and other leading insurance technologies.
Get in touch with us to know more!

Reinventing. Transforming. Scaling – that is what Cloud Native can mean for businesses today!
Cloud-Native can help businesses achieve phenomenal success and improve their ability to deliver more features faster to their customers. It can bring in a major competitive advantage.
This technology increases the velocity of the business and the method to structure their teams to take advantage of automation and scalability.
Are you a business that is starting a digital transformation journey? Or are you wondering what Cloud Native is and why you need it?
This blog describes the advantages of Cloud Native capabilities to speed up your productivity and increase your company’s innovation output. It also discusses upcoming trends to look for.
Read more: Unlocking Opportunities with Cloud Continuum!

Can Moving to a Cloud-Native Approach Improve Business Agility?

Most organizations today are in the midst of a massive data transformation to out-innovate their rivals. The Cloud Native approach allows organizations to build modern applications by leveraging its benefits based on the pay-as-you-go pricing model.
Here is how moving to a Cloud-Native approach improves your business agility:

1. Increased Reusability Reduces Development Costs

Moving to the Cloud Native approach enables developers to build apps that function like building blocks that can be used later for other projects. It makes it easier for developers to access and reuse components created for earlier projects.
How does this improve business agility?

• Simplified development process: Instead of spending time on building the common framework, developers can spend more time on a project’s specifics. This means they can develop more sophisticated applications in less time.
• Faster delivery: All deliveries are time-sensitive. A cloud-native approach enables you to seize the time-sensitive opportunity by reducing the time to market.
• Testing made simple: Cloud-Native uses microservices that present fewer problems. When the load on the pipeline is lightened, the testing is simplified.

2. Better Customer Experience 

Two types of customers are affected by the Cloud Native approach – external customers (those who purchase from you) and internal customers (those development teams).

• Internal customer: Your internal customers or the development teams maintain and manage the systems that your external customers use. Fostering agility in your internal teams improves employee engagement and in turn rewards external customers. Developers are smart people who want to spend their time solving complex problems instead of focusing on just ‘keeping things running.’ The Cloud Native approach automates predictable problems, making better use of your internal team. This allows them to focus more on driving innovation.
• External customers: Building and delivering solutions in response to customer needs will attract and retain customers, in effect building enduring success. Cloud-Native helps find and fix problems faster. It is especially beneficial to businesses with apps that required frequent updates. Cloud-Native gives you a reliable way to deliver those updates in a seamless, resource-efficient manner. This means there is little or no disruption of services during updates while improving responsiveness to the demand they might have.

3. Improved Business Continuity

Downtime can be detrimental to a business’s survival. However, Cloud Native offers a remedy to this. Moving to Cloud-Native keeps operations lean enough to survive whatever turn the market takes.
It also improves business continuity and aids in disaster recovery as it reduces downtime and increases resource availability. It allows employees to work from any location and enables integrated and automated backups. It can also unify processes on a single interface and improve visibility. 

4. Ability to respond to shifting market demands

Cloud-Native is a significant means of spotting an opportunity a moment before a competitor. It provides businesses the ability to respond in hours to sudden changes in the market.
Cloud-Native apps are ideal instruments in turbulent or hypercompetitive markets. Whether a business needs new ways to connect with customers or is undergoing digital transformations, Cloud Native apps enable them to take advantage of sudden opportunities in the market.

Read more: Cloud-Native Application Development: How It’s Powering App Delivery

A Look into The Cloud Native Upcoming Trends

Here are the most relevant Cloud-Native trends businesses can watch out for:

1. Serverless Computing 

Serverless computing is a next-gen technology that ensures agility, cost-effectiveness, and scalability. Essentially, it is a new way of running applications and services that enables developers to focus on building customer-centric applications and optimizing application design.
The operational cost of serverless computing is much lower as it enables IT and development teams to work together. It allows them to share the responsibility of developing and maintaining a product.

2. Distributed Cloud or Multicloud

Another noteworthy trend is the adoption of distributed cloud. It is a method that combines the benefits of the public cloud with an organization’s ability to maintain governance of the infrastructure.
Distributed cloud or Multicloud allows businesses to use the infrastructure of multiple cloud providers simultaneously. You can leave IT management to the providers by deciding the location of the individual services and data archives.

3. Composable application

In the future, businesses will have to free themselves from the rigid divisional barriers that are not compatible with the flexibility of organizations.
A composable application will allow for a more modern software design and organization model. This will allow businesses to quickly create and dispose of the features that are according to the specific business needs.

4. Law-code or No-code

The ability to perform multiple business operations with minimum dependency on the technology team is key to business growth and sustainability.
Using Kubernetes, organizations can create flexible solutions that extensively use low-code or no-code tools. Given that, the non-technical team is free to focus on their roles without specific programming skills.
Read more: A Comprehensive Guide To Modern Cloud Application Development

Become Future Ready

The Cloud Native approach proposes a truly effective model and makes business innovation through the integration of applications.
To embrace the benefits of the cloud, be ready to embrace changes within your entire project lifecycle.  In other words, adopting Cloud Native applications means being ready to welcome future developments in cloud services.
It means opening the doors to opportunities for the future digital business. The cloud-native approach not only helps business innovate faster but help them react to marketplace events with more agility. Wondering how to make this happen for your business?
Let’s have a chat!

The COVID-19 pandemic has accentuated the need for resilient supply chains and human-machine collaboration at work. Full or partial shutdowns, as well as social distancing regulations, impose factories and workspaces to operate with the minimal onsite crew. Despite labor shortages, supply chain disruptions, and other production challenges, manufacturers are under constant pressure to respond to the evolving market needs. The demands for mass customization, quality expectations, faster product cycles, and product variability are at an all-time high. Tackling these persistent challenges requires combining human skill and ingenuity with the strength and speed of robots. To bring the best of both worlds – human creativity and robotic precision – manufacturers should adopt cobots (collaborative robots) that can reduce human interaction in feasible situations and accelerate production cycles.
Cobots allow manufacturers to maximize production and address the changing demands while ensuring the safety of their employees, clients, and partners. Why are cobots the future of manufacturing? How do they help build manufacturing resilience? Let’s explore further in this blog.
Read more: What are cobots and how can they benefit industries

Cobots Enhance Manufacturing Efficiency

Collaborative robots or cobots are designed to safely work alongside humans in tedious, dull, and hazardous environments. Unlike the traditional industrial robots that work in fenced premises to avoid close proximity with people, cobots operate in a shared workspace alongside human labor. For instance, a robot that helps humans sort foam chips in a lab is a cobot, while a robot welding a sharp cutting tool in a restricted factory area is a typical industrial robot.
Conventional industrial robots have long enabled manufacturers to leverage automation and compensate for labor shortages, but they are typically designed to execute one specific task. Moreover, they lack the cognitive capabilities possessed by humans to reprogram their operations based on new circumstances. In contrast, cobots don’t require heavy, pre-programmed actuators to drive them. Cobot motions are steered by computer-controlled manipulators, such as robotic arms, which are supervised by humans. Thus, cobots facilitate effective human-machine collaboration at work.
Cobots can be programmed to perform a wide range of tasks in a factory setting such as handling materials, assembling items, palletizing, packaging, and labeling, inspecting product quality, welding, press-fitting, driving screws and nuts, and tending machines. While cobots attend these mind-numbing jobs, human workers can focus on tasks that require immense resourcefulness and reasoning.
Read more: Digital Transformation in Manufacturing 

Benefits of Cobots in Manufacturing 

Modern manufacturing requires effective human-machine collaboration to cut expenses, reduce time-to-market, and address growing customer demands. Here’s how cobots empower manufacturing enterprises.
1. Easy to Deploy and Program
It takes days and weeks to install and program a traditional industrial robot. A cobot, on the other hand, can be set up in less than an hour. They are lighter than conventional robots. With user-friendly mobile applications and customized software, you can swiftly program the cobot to get started. Right software configurations enable cobots to learn new actions, without any specialized training. Using intuitive 3D visualizations or simple graphical representations, you can move the robot arm to preferred waypoints. Your employees can focus on more critical tasks while the cobot takes care of mundane jobs.
2. Flexible to Perform Different Tasks
Cobots can be easily shifted from one workstation to another due to their flexible hardware. With minimal software customizations, cobots can be re-deployed or repurposed to perform different functions across various departments. For example, a cobot that performs picking and packing can be re-programmed as a filler by replacing its robotic arm with a tube and nozzle.
Read more: Challenges, Opportunities, and Technologies That Will Revolutionize Manufacturing 

3. Save Production Cost and Time
A study conducted by the World Economic Forum in association with Advanced Robotics for Manufacturing found that collaborative robots can cut nearly two-thirds of the cycle time required to pack boxes onto pallets. Because cobots are designed to work without any breaks, they reduce the idle time between cycles. The International Society of Automation reports that cobots can save production costs by reducing 75% of manual labor. Traditional robots increase the installation costs for manufacturers as they need to set up additional safety measures around the deployment area. Cobots don’t incur such extra expenses as they can be set up in close proximity to humans.
4. Improve Employee Engagement and Productivity
Cobots work in collaboration with people to refine and process the tasks better. They can never replace the human touch in production. When cobots take care of repetitive tasks such as screwing a bottle or packing medical equipment, employees can focus on more important functions such as running quality checks or inspecting a worksite. It allows manufacturers to optimize their productivity and boost employee morale. Businesses can also prepare their workforces to learn new skills.
5. Maintain Consistency and Accuracy
From the first to the hundredth task, cobots maintain the same level of accuracy and consistency. Humans can get drained easily, whereas a cobot never deviates from the actions for which it is set up. This helps ensure high product quality and uniformity. With the right software and hardware configurations, cobots can produce more finished goods at an incredible pace, faster than handcrafting.

Cobots and The Future of Manufacturing

Industry 4.0 paved the way for automation and smart manufacturing powered by data-driven technologies such as IoT, cyber-physical systems, wearables, AR, cloud computing, artificial intelligence, cognitive computing, and so on. Though the sole focus of Industry 4.0 is to improve process efficiency through physical and digital integration, it accidentally ignores the significance of human value in process optimization. Industry 5.0 re-shifts its focus on human value by fusing the roles of mechanical components and human workers in production. This makes cobots the very foundation of the next wave of the industrial revolution, that is, Industry 5.0.
Denmark-based Universal Robots reports that cobots are at the heart of Industry 5.0. Cobots democratize robotic capabilities, thereby serving as a personal tool that can be leveraged by any member of the workforce to apply creative skills and generate more value. Cobots can be used as a plug-and-play solution across a variety of manufacturing and industrial operations such as automotive production, food processing, chemical plants, medical devices, and kits, among others.
Since they collaborate well with humans in a safe environment, cobots will:

• augment intelligent decision-making,
• drive high-quality products to the market,
• enable mass customization and personalization,
• optimize manufacturing costs,
• generate new job roles (eg: Chief Robotics Officer), and
• boost virtual education to make the most of collaborative robotics.

Read more: How Custom Software Development Helps Manufacturing Industry 

How We Help Manufacturers Leverage Cobots and Other Emerging Technologies

As technology matures, manufacturing enterprises need to build use cases that prove the inevitability of human-robot collaboration. We help develop POCs and use cases that demonstrate how your business can benefit from cobots. Our experts can develop your cobot management software or mobile app from scratch or customize your existing software to address the evolving market demands. Fingent custom software development company can work along with your cobot hardware manufacturers to develop a robust software orchestration layer that can control the movement of your cobots. We also simplify the training process to help you get started in no time.