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Is AI Disruption on the way for Kenya’s Insurance Space?

The earliest known reason for introducing insurance protection in Kenya, came during the time of the Colonial British — when they insured their farms and crops against loss, damage etc. Today, Kenya has 70% of the East African Insurance market (among Burundi, Uganda, Tanzania & Rwanda). Still, African Insurance is relatively nascent in terms of size. Only 6 major markets dominate the landscape in a serious way — Egypt, Tunisia, Morocco, South Africa, Nigeria & Kenya. Infact, the number of insurtech startups in the continent altogether is a paltry 50 something. 

The looming political climate coupled with a slowly recovering economy and some fierce competitive tactics used by traditional incumbents places the industry far from ideal in terms of marketplace conditions, including the slowdown in uptake of insurance products by an income-sensitive population.

Yet, Kenya offers a sense of growing appeal for young insurtechs in this region. The market remains largely undisrupted, since insurance penetration is only about 3% (insurance penetration for the African continent is only at 0.3%), attracting large international insurers like Allianz and Swiss Re who have recently entered the market. Kenya, like other countries in the region, has enormous potential similar to South-East Asian economies that also remain largely undisrupted with lower penetration rates.

The positive sentiment surrounding Kenya’s potential for deep tech disruption is not surprising — According to the 2019 Government AI Readiness Index published by the  IDRC and Oxford Insights — Kenya is the most AI ready country in Africa.

Buying Behavior

Insurtech startups are exploring avenues using AI that large, traditional players have less incentive to exploit, such as offering ultra-customized policies, social insurance, and using behavior data from devices to dynamically price premiums.

The Millennial experience is entirely technology driven, while their attitudes and perceptions as consumers will shape the future of how insurance as a service continues to remain relevant.


According to a Kenya Insurance Industry Report, 65% of millennials compare prices across different websites before making a purchase, 68% only buy a product through referrals from friends and social media. Interestingly, 84% of them are opposed to traditional advertising. 

For insurers, loyalty comes at a price — often dictated by the pain point the product/service can eliminate for impatient classes of customers. Analysing buying or browsing behavior can lead to an immense amount of ethically siphoned data. Using ML models and regression algorithms, insurers can create a unified view of their prospect, and realize a multi-targeted approach to create opportunities for upselling or cross-selling.


The report also highlights the importance of making sense of social media behavior — since 41% of millennials use social networking sites to pass on recommendations of products and services to friends and family.

Unlocking market potential requires targeting the uninsured growing middle class in creative ways. In addition to better pricing models, insurtech startups are testing the waters on a host of potential game-changers, such as using deep learning trained artificial intelligence (AI) to handle the tasks of brokers and finding the right mix of policies to complete an individual’s coverage.

Insurtechs are using AI to solve for Kenya’s distribution challenges, by looking at vital consumer needs that have previously been unmet or glossed over. At the same time, there is scope for improving the average consumer’s awareness of artificial intelligence technology, and how they can take advantage of it to solve priority-first issues related to convenience, cost and range of choice.
Nairobi-based Jubilee Insurance, the largest insurer in East Africa is making the most of AI tools like chatbots and automated messaging platforms for streamlining simple customer feedback & support operations. They have also launched forward-thinking products like “Recover in Style” which provides hair and make-up services to Jubilee patients who are hospitalized — services that go beyond the financial needs and into the realm of delivering superior customer experiences.

These efforts highlight a trend pointing towards the growing interest in the use of apps to pull policies into one platform for management and monitoring, creating on-demand insurance for micro-events like borrowing a friend’s car, and the adoption of the peer-to-peer models to create customized coverages. Bluewave, for example, is an insurtech startup offering low-cost insurance products, as low as US$4 a week, aimed at low-resource, low-income users in last-mile environments.

The expanding middle class and growth in mobile phone penetrations will be critical to widening distribution and getting more people to buy micro-insurance sized products for the first time. Badalaa is an on-demand insurtech startup focussed on bringing insurance at the point of transaction where the user needs it. Turaco, a recently funded insurtech, with premiums for as little as US$2 — leverages mobile financial services to provide hospital cashback to customers who have sought treatment at any nationally-accredited hospital in the regions where they operate. These innovations further the consumer’s awareness of AI-enabled insurance coverage and protection in general, in an otherwise underpenetrated marketplace.


Bismart is another example — an insurtech aggregator that allows customers to not only buy the best-in-class insurance products but also make claims directly from their portal as well. 

The biggest learnings for young insurtechs in this space from more mature markets, are about getting the basics right – having a single view of the customer, being able to launch rates and change pricing in real-time, offering customers a multichannel experience without requiring them to fill in the same information over and over again, and settling claims quickly without the need for multiple touchpoints.

Demand-driven models, built on sufficiently large data-sets will be instrumental in driving individual customisation at mass-scale for the sector at large.

webinar: AI for data-driven Insurers

Join our Webinar — AI for Data-driven Insurers: Challenges, Opportunities & the Way Forward hosted by our CEO, Parag Sharma as he addresses Insurance business leaders and decision-makers on April 14, 2020.

We help young insurtechs, build and scale AI-driven products and solutions for last-mile environments. Reach out to us on hello@mantralabsglobal.com, to learn more.

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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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