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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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Smart Machines & Smarter Humans: AI in the Manufacturing Industry

We have all witnessed Industrial Revolutions reshape manufacturing, not just once, but multiple times throughout history. Yet perhaps “revolution” isn’t quite the right word. These were transitions, careful orchestrations of human adaptation, and technological advancement. From hand production to machine tools, from steam power to assembly lines, each transition proved something remarkable: as machines evolved, human capabilities expanded rather than diminished.

Take the First Industrial Revolution, where the shift from manual production to machinery didn’t replace craftsmen, it transformed them into skilled machine operators. The steam engine didn’t eliminate jobs; it created entirely new categories of work. When chemical manufacturing processes emerged, they didn’t displace workers; they birthed manufacturing job roles. With each advancement, the workforce didn’t shrink—it evolved, adapted, and ultimately thrived.

Today, we’re witnessing another manufacturing transformation on factory floors worldwide. But unlike the mechanical transformations of the past, this one is digital, driven by artificial intelligence(AI) working alongside human expertise. Just as our predecessors didn’t simply survive the mechanical revolution but mastered it, today’s workforce isn’t being replaced by AI in manufacturing,  they’re becoming AI conductors, orchestrating a symphony of smart machines, industrial IoT (IIoT), and intelligent automation that amplify human productivity in ways the steam engine’s inventors could never have imagined.

Let’s explore how this new breed of human-AI collaboration is reshaping manufacturing, making work not just smarter, but fundamentally more human. 

Tools and Techniques Enhancing Workforce Productivity

1. Augmented Reality: Bringing Instructions to Life

AI-powered augmented reality (AR) is revolutionizing assembly lines, equipment, and maintenance on factory floors. Imagine a technician troubleshooting complex machinery while wearing AR glasses that overlay real-time instructions. Microsoft HoloLens merges physical environments with AI-driven digital overlays, providing immersive step-by-step guidance. Meanwhile, PTC Vuforia’s AR solutions offer comprehensive real-time guidance and expert support by visualizing machine components and manufacturing processes. Ford’s AI-driven AR applications of HoloLens have cut design errors and improved assembly efficiency, making smart manufacturing more precise and faster.

2. Vision-Based Quality Control: Flawless Production Lines

Identifying minute defects on fast-moving production lines is nearly impossible for the human eye, but AI-driven computer vision systems are revolutionizing quality control in manufacturing. Landing AI customizes AI defect detection models to identify irregularities unique to a factory’s production environment, while Cognex’s high-speed image recognition solutions achieve up to 99.9% defect detection accuracy. With these AI-powered quality control tools, manufacturers have reduced inspection time by 70%, improving the overall product quality without halting production lines.

3. Digital Twins: Simulating the Factory in Real Time

Digital twins—virtual replicas of physical assets are transforming real-time monitoring and operational efficiency. Siemens MindSphere provides a cloud-based AI platform that connects factory equipment for real-time data analytics and actionable insights. GE Digital’s Predix enables predictive maintenance by simulating different scenarios to identify potential failures before they happen. By leveraging AI-driven digital twins, industries have reported a 20% reduction in downtime, with the global digital twin market projected to grow at a CAGR of 61.3% by 2028

4. Human-Machine Interfaces: Intuitive Control Panels

Traditional control panels are being replaced by intuitive AI-powered human-machine interfaces (HMIs) which simplify machine operations and predictive maintenance. Rockwell Automation’s FactoryTalk uses AI analytics to provide real-time performance analytics, allowing operators to anticipate machine malfunctions and optimize operations. Schneider Electric’s EcoStruxure incorporates predictive analytics to simplify maintenance schedules and improve decision-making.

5. Generative AI: Crafting Smarter Factory Layouts

Generative AI is transforming factory layout planning by turning it into a data-driven process. Autodesk Fusion 360 Generative Design evaluates thousands of layout configurations to determine the best possible arrangement based on production constraints. This allows manufacturers to visualize and select the most efficient setup, which has led to a 40% improvement in space utilization and a 25% reduction in material waste. By simulating layouts, manufacturers can boost productivity, efficiency and worker safety.

6. Wearable AI Devices: Hands-Free Assistance

Wearable AI devices are becoming essential tools for enhancing worker safety and efficiency on the factory floor. DAQRI smart helmets provide workers with real-time information and alerts, while RealWear HMT-1 offers voice-controlled access to data and maintenance instructions. These AI-integrated wearable devices are transforming the way workers interact with machinery, boosting productivity by 20% and reducing machine downtime by 25%.

7. Conversational AI: Simplifying Operations with Voice Commands

Conversational AI is simplifying factory operations with natural language processing (NLP), allowing workers to request updates, check machine status, and adjust schedules using voice commands. IBM Watson Assistant and AWS AI services make these interactions seamless by providing real-time insights. Factories have seen a reduction in response time for operational queries thanks to these tools, with IBM Watson helping streamline machine monitoring and decision-making processes.

Conclusion: The Future of Manufacturing Is Here

Every industrial revolution has sparked the same fear, machines will take over. But history tells a different story. With every technological leap, humans haven’t been replaced; they’ve adapted, evolved, and found new ways to work smarter. AI is no different. It’s not here to take over; it’s here to assist, making factories faster, safer, and more productive than ever.

From AR-powered guidance to AI-driven quality control, the factory floor is no longer just about machinery, it’s about collaboration between human expertise and intelligent systems. And at Mantra Labs, we’re diving deep into this transformation, helping businesses unlock the true potential of AI in manufacturing.

Want to see how AI-powered Augmented Reality is revolutionizing the manufacturing industry? Stay tuned for our next blog, where we’ll explore how AI in AR is reshaping assembly, troubleshooting, and worker training—one digital overlay at a time.

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