Click-Ins

An AI vehicle-inspection platform trained on synthetic data that detects and quantifies damage, producing inspection reports in real time for leasing, insurance, and dealers

4.1 Israel
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What is it

Click-Ins is an Israeli AI vehicle-inspection platform distinguished by training its models on synthetic data. It can detect and measure vehicle damage and produce inspection reports in real time, serving leasing, insurance, and dealers. Training on synthetic data means it can cover a large variety of damage and scenario types, filling the gap where real data is hard to collect comprehensively.

What problem it solves

Manual inspection is subjective, easy to miss, and hard to standardize, and delivery/return and claims often spark arguments over "does this scratch count, and how big." Click-Ins uses AI not only to detect damage but to further measure the extent of damage and generate inspection reports in real time, so vehicle condition has an objective, comparable record. It suits scenarios needing large-scale, standardized inspection like leasing companies' return checks, insurance claims, and dealers' used-car assessment. Note that measurement and detection accuracy is still affected by shooting angle, lighting, and dirt; report results mostly serve as evidence, and claim amounts and liability still need human gatekeeping; this space is crowded with competitors, so it's advised to real-test recognition rate and report format before adopting. Overall, it's an inspection tool focused on objective quantification of vehicle damage.

Key Features

  • Trains models on synthetic data
  • Detects and measures vehicle damage
  • Produces inspection reports in real time
  • Serves leasing, insurance, and dealers
  • Provides objective, comparable condition records

Pros

  • Can quantify damage extent, not just its presence
  • Real-time reports speed inspection and claims
  • Synthetic-data training covers diverse damage scenarios

Cons

  • Accuracy still affected by shooting angle, lighting, and dirt
  • Reports mostly serve as evidence; amount and liability still need human judgment

Use Cases

  • Leasing companies' condition checks at delivery and return
  • Insurance claims needing objective damage-quantification evidence
  • Dealers' used-car assessment needing standardized inspection

Editor's Note

An inspection platform focused on quantifying vehicle damage and trained on synthetic data — easy for the leasing and insurance sides to adopt.

FAQ

What's the benefit of synthetic-data training?

It can cover a large variety of damage and scenario types, filling the gap where real data is hard to collect comprehensively.

Does Click-Ins only judge whether there's damage?

Not only — it detects and measures the extent of damage, giving vehicle condition a comparable quantified record.

Can the report be used directly as a claims basis?

Reports mostly serve as objective evidence; the actual claim amount and liability still need human review and gatekeeping.

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