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Alex Dalyac: Revolutionizing Accident Recovery with Computer Vision at Tractable
June 2022

It's such common advice that it is practically a cliche to tell founders to take inspiration from customer problems that can be solved – and never to approach building a product as a technological hammer in search of a nail. Luckily for fintech unicorn Tractable, co-founders Alex, Adrien, and Raz ignored that advice when starting their company. They had an instinct about the utility of computer vision applications deployed in the real world, and successfully pursued it, building a billion-dollar business in the process.

In 2012, there were several significant breakthroughs in deep learning. In the ImageNet Large Scale Visual Recognition Challenge, a convolutional neural network halved the existing error rate on ImageNet visual recognition and proved out several new techniques, including the use of GPUs to train a model. This and several other related developments around that period led to meaningful performance improvements in computer vision and really shifted the possibilities for its application.

Investors often talk about the importance of market timing, but Tractable had the ideal technology timing — they caught the wave of the rise of this new technology right when it was just beginning to be commercially feasible (with enough focus and expertise) and before it was commonplace. Alex Dalyac, Tractable’s CEO, and the co-founding team were maniacal about identifying and pursuing a specific vertical use case for computer vision technology that delivered tremendous customer value: damage appraisal for accident recovery, starting first with cars and homes. They understood the compounding effects of large-scale datasets in improving the accuracy of their models, and prioritized pursuing a specific segment of the market with access to that data in mind.

Alex walks us through how he and his co-founders Razvan Ranca and Adrien Cohen set out to start a company based on specific machine learning techniques; how they moved from applications in radiology to insurance appraisal in their initial research process; and how they developed a product into a scalable business that has grown Tractable into the breakout applied AI company that it is today.

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