Mitchell has announced the availability of Mitchell Cloud Estimating in Canada. Carriers and collision repairers can use the cloud-based application to write estimates from anywhere and from any Internet-enabled Microsoft Windows, Apple iOS or Google Android device – including their smartphone, tablet or laptop.
To help ensure appraisal accuracy and the delivery of proper, safe vehicle repairs, Mitchell Cloud Estimating also provides seamless access to integrated OEM repair procedures as the estimate is developed, reducing research time. The solution operates within Mitchell’s Connect platform where vehicle images and scans from Mitchell Diagnostics are available in the card-based user interface. Additionally, the scalable, cloud-based architecture allows insurers and collision repairers to quickly deploy Mitchell Cloud Estimating across their organizations, simplifying the transition to a new appraisal system, lowering development and maintenance costs, and providing immediate access to the latest product features.
First delivered to the U.S. market, Mitchell Cloud Estimating now supports Canadian:
- Parts and pricing
- Language localization
- Tax configurations
- Provinces and postal codes
“Mitchell has always been committed to providing an open, cloud-based platform that allows our customers to work more efficiently while remaining focused on proper and safe repair,” said Debbie Day, executive vice president and general manager of Mitchell’s Auto Physical Damage division. “Mitchell Cloud Estimating and its availability across North America is a perfect example of how we’ve delivered on that commitment and met the goals we set out to achieve with Program Freedom and our open ecosystem of cloud solutions.”
Mitchell Cloud Estimating provides a choice of EMS or BMS standards for data sharing as well as offers VIN scanning, photo integration and the ability to write multiple appraisals at once. The cloud-based system also integrates with the Mitchell Intelligent Estimating solution, which automates the appraisal process by leveraging artificial intelligence to transform images of damaged vehicles into component-level estimate lines.
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