Innovation & AI: Real-Time Asset Intelligence with Eliron Ekstein

From Energy Labs to AI: Eliron Ekstein on the Evolution of Real-Time Asset Intelligence

In a high-stakes episode of Risk Management: Brick by Brick, host Jason Reichl sits down with Eliron Ekstein, co-founder and CEO of Raven.AI, to explore the transformation of vehicle inspections through advanced computer vision. With a history that began in a Shell energy technology lab, Ekstein provides a unique perspective on how a "lucky coincidence" led to a data-rich system that is now reshaping the insurance claims landscape.

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The Pivot from Lab to Fleet Management

While many startups begin with a rigid product vision, Raven.AI was born out of a pivot. Originally a project within a Shell lab to upsell tires and oil through car scanning, the team quickly realized the business model wasn't there.

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The turning point came when rental giants like Avis and Hertz noticed the technology. "They said, 'why don't you come over and install the system in our locations and start tracking damage?'" Ekstein recalls. This shift into the fleet industry allowed Raven.AI to build a massive, holistic dataset that eventually made them a perfect fit for the insurance sector.

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The "Trust Gap" and the 360-Degree Advantage

A recurring challenge for AI in insurance is the lack of trust from customers and adjusters. Ekstein argues that the key to bridging this gap is not just better algorithms, but better evidence.

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Unlike traditional assessments that rely on a single photo of a broken bumper, Raven.AI utilizes a full 360-degree scan. "It's all about transparency, giving the grounds for your decision and giving evidence," Ekstein asserts. By providing high-fidelity images and zoomed-in details from multiple angles, the system justifies its decisions to both the insurer and the policyholder.

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The 80/20 Future of Claims

Looking ahead, Ekstein is bullish on the "80/20 rule" for claims automation. He predicts that in the next five years, 80% of claims will feature 80% automation, while the remaining 20% will be flagged for human adjusters to handle complex or high-severity reviews.

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This shift is increasingly necessary as claim severity rises. While automated safety systems (ADAS) may slightly decrease the frequency of accidents, the cost to repair modern, camera-laden vehicles is "through the roof". As Ekstein notes, "Every crash will merit more investigation".

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Shrinking the Cycle Time

The real-world impact of this technology is already being felt in the velocity of claims. By moving to a self-service model where policyholders scan their own vehicles, Raven.AI has helped customers reduce average cycle times from 14 days to less than seven. This efficiency translates directly into massive savings on rental car costs, storage fees, and litigation.

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Advice for the Next Generation: Solve Real Problems

For those looking to innovate in the InsurTech space, Ekstein’s advice is simple: prioritize real-world experience over pure academia. Despite having two degrees himself, he advocates for getting "hands dirty" in the industry for five or six years before trying to fix it.

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"You need to understand the problem before you can solve the problem," he concludes. In an industry where rising repair costs and complex assets like autonomous vehicles are the new normal, the ability to combine deep industry knowledge with transparent AI will be the ultimate differentiator.

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To hear the full discussion on 360-degree data and the future of automated claims, tune in to this episode of Risk Management: Brick by Brick.

👉 Spotify: https://tinyurl.com/4p5nccc6 

👉 Apple Podcasts: https://tinyurl.com/5dr4jchr 

 👉 YouTube: https://youtu.be/SNc1rGZ_xrw 

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Podcast Host: Jason Reichl 

Executive Producer: Don Halliwell