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The Adoption of Chatbots across Insurance

The global chatbot market is expected to reach USD$ 1.25B by 2025, and generate roughly $8B savings globally by 2022 itself. With chatbots disrupting a wide variety of industries already, the technology is becoming more popular in a variety of business use cases – especially within the insurance sector.

Chatbots are becoming more advanced

Chatbots are a natural extension of the push for self-service capabilities. Yet in spite of its growing popularity, according to a recent white paper published by Cognizant Research, almost 60% of insurers surveyed worldwide are yet to implement a chatbot. According to Cognizant’s research (validated with our own internal findings), bot capability is derived from the maturity of the bot; either basic, moderate or advanced.

What makes chatbots effective

Based on this spectrum, ‘basic’ implies that a bot is mostly rules-based and can follow only simple instructions often deferring to a human, whereas those bots that are closest to a true human-like conversation, are classified as ‘advanced’ in terms of their capability. The maturity level of the bot is determined by their performance and their ability to Communicate, Comprehend and Collaborate with the user, providing utility across the value chain. These three C’s are key factors in distinguishing an effective bot from an unsatisfactory one.

Of insurers that have utilized chatbots in their operations, a majority 68% utilise only a basic form of the technology. While insurers have already benefited by saving costs and reducing customer servicing time using them, there is still significant opportunity for the uptake of more capable, reliable and intelligent bots to be deployed across the insurance value chain.

Europe has the highest volume of basic maturity chat bots among insurers at 60%. Asia along with MEA promises the most potential in terms of size and CAGR to adopt chat bot technologies over the next five years. North America is still the largest consumer of ‘advanced’ bots in insurance compared to all other regions.

Chatbots – leading CONSUMER AI APP for the next 5 years

Limitations to overcome

Insurers need to focus on these limitations faced by chatbots to realize their business imperative.

  • Need of human-centric interface: Most of the time, interactions with chatbot are still robotic, providing the end-user with a frustrating non-human centric experience.
  • Inability to contextualize conversations: Bots are programmed to follow a specific sequence or an algorithm, causing an inability to understand the nuances of human language – that results in an unfulfilling and an inauthentic experience.
  • Scalability issues: Developers need to anticipate and program the bot according to the exponential rise in the amount of traffic that the bot might handle.
  • Privacy and data protection: Data is both an asset and a liability. Since customers often give away personal data while conversing with a chatbot, insurers need to prioritise their privacy and data protection regulations for that region.

Opportunity Landscape for AI-enabled Chatbots

Chatbots can be leveraged for both simple and complex insurance processes in order to create definitive business value. Distinct successes have been noted in areas of:

AI Chatbot in Insurance Report

AI in Insurance will value at $36B by 2026. Chatbots will occupy 40% of overall deployment, predominantly within customer service roles.
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Insurtechs will lead the pack

Among other reasons for the large-scale implementation of chatbots, is that insurtechs predominantly target the tech-savvy millennial and Gen Z population who are more open to change and disruptive innovation. Positive customer experiences are directly proportional to twice the referrals, thereby expanding business scope by breaking traditional customer-interaction limitations.

Reimagining Insurance with Chatbots

The insurance industry has reached a revolutionary crossroad that mandates insurers become digitally agile. Over the next few years, chatbots are set to bring about a massive change to the industry and Insurtechs are leading the way in bringing AI-powered chatbots to the insured customer.

  • Lemonade: The NY-based insurtech relies on its app-based chatbots, backed by AI, that can craft personalized insurance policies & quotes for customers, and respond swiftly to a variety of customer queries and process claims.
  • Next Insurance: The insurance provider launched a chatbot via Facebook Messenger through which small businesses can obtain quotes and buy insurance.
  • Trōv: The company has integrated a chatbot into its mobile app that handles customer queries and claims by seamlessly gathering incident related information from the customer.
  • LeO: The insurer recently launched a chatbot which helps schedule calls and meetings, collect leads and answer customer questions automatically – allowing agents to focus on other tasks.
  • Religare: It’s one of the top health insurers in India and a part of major financial service conglomerate. The company has integrated an AI empowered insurance chatbot, that focuses on learning from actual human interactions over a question-answer driven format to build a more intuitive chat based sales funnel.

There is a direct relation between the positive Customer Experience provided by the chatbots and the hike in the revenues. Almost one-third of the insurance business is expected to be generated via digital channels in the next 5 years. The companies that leverage AI-driven customer data for chatbots shall flourish far into the future.

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Why Netflix Broke Itself: Was It Success Rewritten Through Platform Engineering?

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Let’s take a trip back in time—2008. Netflix was nothing like the media juggernaut it is today. Back then, they were a DVD-rental-by-mail service trying to go digital. But here’s the kicker: they hit a major pitfall. The internet was booming, and people were binge-watching shows like never before, but Netflix’s infrastructure couldn’t handle the load. Their single, massive system—what techies call a “monolith”—was creaking under pressure. Slow load times and buffering wheels plagued the experience, a nightmare for any platform or app development company trying to scale

That’s when Netflix decided to do something wild—they broke their monolith into smaller pieces. It was microservices, the tech equivalent of turning one giant pizza into bite-sized slices. Instead of one colossal system doing everything from streaming to recommendations, each piece of Netflix’s architecture became a specialist—one service handled streaming, another handled recommendations, another managed user data, and so on.

But microservices alone weren’t enough. What if one slice of pizza burns? Would the rest of the meal be ruined? Netflix wasn’t about to let a burnt crust take down the whole operation. That’s when they introduced the Circuit Breaker Pattern—just like a home electrical circuit that prevents a total blackout when one fuse blows. Their famous Hystrix tool allowed services to fail without taking down the entire platform. 

Fast-forward to today: Netflix isn’t just serving you movie marathons, it’s a digital powerhouse, an icon in platform engineering; it’s deploying new code thousands of times per day without breaking a sweat. They handle 208 million subscribers streaming over 1 billion hours of content every week. Trends in Platform engineering transformed Netflix into an application dev platform with self-service capabilities, supporting app developers and fostering a culture of continuous deployment.

Did Netflix bring order to chaos?

Netflix didn’t just solve its own problem. They blazed the trail for a movement: platform engineering. Now, every company wants a piece of that action. What Netflix did was essentially build an internal platform that developers could innovate without dealing with infrastructure headaches, a dream scenario for any application developer or app development company seeking seamless workflows.

And it’s not just for the big players like Netflix anymore. Across industries, companies are using platform engineering to create Internal Developer Platforms (IDPs)—one-stop shops for mobile application developers to create, test, and deploy apps without waiting on traditional IT. According to Gartner, 80% of organizations will adopt platform engineering by 2025 because it makes everything faster and more efficient, a game-changer for any mobile app developer or development software firm.

All anybody has to do is to make sure the tools are actually connected and working together. To make the most of it. That’s where modern trends like self-service platforms and composable architectures come in. You build, you scale, you innovate.achieving what mobile app dev and web-based development needs And all without breaking a sweat.

Source: getport.io

Is Mantra Labs Redefining Platform Engineering?

We didn’t just learn from Netflix’s playbook; we’re writing our own chapters in platform engineering. One example of this? Our work with one of India’s leading private-sector general insurance companies.

Their existing DevOps system was like Netflix’s old monolith: complex, clunky, and slowing them down. Multiple teams, diverse workflows, and a lack of standardization were crippling their ability to innovate. Worse yet, they were stuck in a ticket-driven approach, which led to reactive fixes rather than proactive growth. Observability gaps meant they were often solving the wrong problems, without any real insight into what was happening under the hood.

That’s where Mantra Labs stepped in. Mantra Labs brought in the pillars of platform engineering:

Standardization: We unified their workflows, creating a single source of truth for teams across the board.

Customization:  Our tailored platform engineering approach addressed the unique demands of their various application development teams.

Traceability: With better observability tools, they could now track their workflows, giving them real-time insights into system health and potential bottlenecks—an essential feature for web and app development and agile software development.

We didn’t just slap a band-aid on the problem; we overhauled their entire infrastructure. By centralizing infrastructure management and removing the ticket-driven chaos, we gave them a self-service platform—where teams could deploy new code without waiting in line. The results? Faster workflows, better adoption of tools, and an infrastructure ready for future growth.

But we didn’t stop there. We solved the critical observability gaps—providing real-time data that helped the insurance giant avoid potential pitfalls before they happened. With our approach, they no longer had to “hope” that things would go right. They could see it happening in real-time which is a major advantage in cross-platform mobile application development and cloud-based web hosting.

The Future of Platform Engineering: What’s Next?

As we look forward, platform engineering will continue to drive innovation, enabling companies to build scalable, resilient systems that adapt to future challenges—whether it’s AI-driven automation or self-healing platforms.

If you’re ready to make the leap into platform engineering, Mantra Labs is here to guide you. Whether you’re aiming for smoother workflows, enhanced observability, or scalable infrastructure, we’ve got the tools and expertise to get you there.

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