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How Machine Vision can Revolutionize Motor Insurance

3 minutes, 49 seconds read

The motor insurance market in India is approximately Rs 70,000 crore in terms of Gross Written Premiums. With newer and stricter regulations more and more people are buying motor insurance. However, while motor insurance, in general, has grown by 16% over the last year, the new digital insurers in the marketplace have seen their premiums increase by 4X-6X. 

This underlines a shift in the way customers choose to buy motor insurance – from the convenience of their smartphone or computer, instantly. There is no reason to think that they would not want to settle an insurance claim in the same convenient manner. Fortunately, machine vision technology solves claims settlement challenges to a great extent.

Current Claims Process

Let us have a quick look at the current claim settlement process for motor insurance. Once the accident occurs, the insured has to follow the following steps:

  1. The insured informs the insurance company about the accident. Subsequently, the insured files a physical claim along with the required documents such as RC, DL, insurance policy, bills, receipts, etc.
  2. A surveyor gets assigned by the insurance company to examine the damaged vehicle. 
  3. The surveyor ascertains the reason and the extent of the loss. After this, the insurer sends an approval/rejection of the claim/amount.

The above process is not only time consuming and stressful for the insured but also expensive for the insurer due to physical inspection and other manual checks and balances. The higher cost of processing the claim makes business less profitable to the insurer. The inconvenience and long wait make the product less desirable to the customer.

As more and more people buy motor insurance online, the customer expectation from the claim settlement process is changing as well. Customers now expect a seamless digital claim settlement process preferably in a matter of hours if not minutes, instead of the present industry standard of several days.

A Machine Vision Solution to Instant Claims Processing: FlowMagic

We at FlowMagic set out to solve this problem both for the insured and insurer using the power of artificial intelligence. We have used machine vision to eliminate the need for the surveyor in all but the most complex cases. 

Using machine vision, we can process a car image and identify not only the damaged parts but also the severity of damage to those parts and whether it requires repair or a replacement. We have further analyzed repair cost data and images from tens of thousands of accident cases to build an Artificial Intelligence Costing Model that can estimate the cost of repairing any part just by looking at its photograph. All this means that the insurer doesn’t need the surveyor and other manual checks in most cases and the customer can submit a claim from the convenience of his smartphone and get an approval decision within minutes.

New Claims Settlement Process with FlowMagic

  1. After the accident, the customer clicks photographs of damaged parts of the car and uploads them on the app along with a photo of DL/RC.
  2. The AI model verifies the DL/RC information and estimates the extent of damage to the car and whether the damaged parts need to be replaced or repaired. The model further calculates the cost of repair and/or replacement and informs the customer/insurance company.
  3. Based on the outcome of the DL/RC verification and the repair estimate the claim is either auto-approved in minutes or forwarded to a claims adjuster for review.

All the stakeholders in the insurance value chain can use our solution and benefit from it.

Insurance Company: By integrating this solution with mobile applications, Insurance companies can get quick claims intimations and a reasonable estimate of the repair cost. The damage severity analysis also helps the insurance company negotiate with the garage on whether a part needs repair or replacement.

Service Center or Garage: Multi-brand garages or service centers can quickly assess the level of damage to any car brought to them through machine vision-based FlowMagic. Accordingly, they can send a quick quotation to the insurance companies. The insurance companies can trust this quotation as it is generated by a robust AI model.

End Customer: An end customer can also use our free mobile application to get a repair estimate. This can be a starting point for an informed negotiation with a garage.

To learn more about how FlowMagic can transform the way you settle your motor insurance claims or discuss your broader AI goals, please get in touch with us at hello@mantralabsglobal.com 

Also read – How AI can settle insurance claims in less than 5 minutes!

About author: Himanshu Saraf is a Capital Markets Director at Mantra Labs. He also leads Artificial Intelligence (AI) and Machine Learning initiatives in the company.

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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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