AutovistaREPAIR

Comprehensive repair data at your fingertips. Fully compatible with TecDoc data.

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Repair data you can trust

When it comes to quality repair data feeds, Autovista Group truly is the market forerunner.

This is because we spare no expense with collating the very best raw data sets, which we then input into our cutting-edge machine learning technology to give you industry-leading feeds for:

  • Accurately estimating repair costs for any vehicle, so you can protect your margins from parts cost disparity
  • Easily identifying correct parts even if superseded
  • Maximising profitable purchasing/manufacturing margins with instant unlimited access to industry-leading data.

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What's included

Available as a data feed to be used with Autovista Group’s suite of industry-leading products, the repair data package also offers:

  • AZT-sourced paint data* – to correctly estimate the cost of paint jobs
  • New graphic displays* – simply click on any vehicle part to get its price
  • TecDoc compatibility* – so you can use parts codes from the renowned catalogue
  • Local languages – for wider access

*optional extras


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Who is AutovistaREPAIR for?

car remarketing

Fleet operators

Forecast wear parts for any vehicle to factor into Total Cost of Ownership and improve your purchasing strategy, acquiring the most suitable vehicles for your customers’ car park.

Software companies

Use our repair data feeds to build your automotive industry deliverables, such as calculator tools, configurators, and much more.

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Finance

Accurately estimate OEM parts prices to properly valuate the benchmark for repair operations.

fleet telematics

Insurance

Calculate the cost of repair, including for total loss cases, to process claims faster and win more customers.

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Bodyshops

Easily identify the correct vehicle part on our impressive interactive graphic and save time figuring it out manually.

vehicle stock management system

Dealers

Confidently factor repair cost estimates into your margins to avoid losing profit through parts cost disparity.

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