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E-Estimations: Mitchell to sell AI photo estimating tool in 2020

Toronto, Ontario — Oct. 2, 2019 — On Tuesday, Mitchell International announced the release of its Mitchell Intelligent Estimating system, able to “predict and pre-populate all possible proportions of an estimate” from photos.

According to Mitchell, the system uses Google’s computer vision and cloud processing power and allows appraisers to further complete, review and approve a pre-written estimate. The company says its solution generates detailed auto physical damage estimates, including parts, operations and labour details — all based on photos transmitted by a policyholder, repair facility or appraiser. The system will be up for sale beginning in 2020’s first quarter.

“This new transformative estimating solution demonstrates both Mitchell’s key focus on innovation as well as our commitment to embracing the most respected domain experts to accelerate the pace of claims automation,” said Olivier Baudoux, head of global product and artificial intelligence for Mitchell International, in a news release. “The Mitchell Intelligent Estimating solution is the latest display of our commitment to deliver leading-edge solutions and better outcomes for our clients, and underscores Mitchell’s commitment to advancing one of the most complex industry opportunities.”

The system uses an open platform; clients may swap in different software to perform the image analysis instead of using Mitchell’s first-party tech, according to Mitchell’s senior vice president of sales and services, Jack Rozint.

The news comes on the heels of last week’s announcement that USAA has been working with Mitchell and Google Cloud on a jointly developed solution to enable its touchless claims vision.

Rozint has acknowledged that many companies are working on image analysis systems; while Mitchell feels it would be “hubris” to assume its system is the ultimate solution, it says it is certainly working toward that goal.

Click here to learn more about Mitchell’s cloud estimating software.

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