Walk down any automotive production line and you’ll see a paradox: the most advanced robots in the world building vehicles, and humans still squinting to spot cracks in glass or scratches on body panels. The same problem repeats after cars leave the factory—insurers spend billions every year manually validating damage claims, often relying on grainy photos and inconsistent inspections.

At Datadoo, we believe this is a data problem, not a hardware problem. Real-world data is expensive, slow, and always incomplete. Edge cases, the rare but costly defects, are nearly impossible to capture at scale. That’s why we generate synthetic visual and physical data that looks and behaves like the real world, but with unlimited variation, perfect labels, and zero PII.

Defect detection on the line

With synthetic datasets, automakers can train AI to see what humans miss. Micro-cracks in windshields, tiny chips in coatings, subtle misalignments in brackets—all of them can be simulated under different lighting, weather, and camera setups. Because every pixel is labeled automatically, the AI learns faster and with fewer false positives. Models trained on Datadoo data slot directly into production environments, running on the cameras already in place, and keeping pace with takt time.

Insurance without the guesswork

The same technology applies once the car is on the road. For insurers, windshields alone represent nearly 40% of claims. Our AI pipeline turns a short smartphone video into an instant assessment: crack or no crack, repair or replace. Fraud checks, repair routing, and ADAS recalibration readiness are all built into the flow. And because the training data is fully synthetic, insurers can share, scale, and deploy globally without regulatory friction.

Why it matters

• Faster time to value: weeks instead of months to get working models.

• Lower costs: no armies of human labelers, no endless field collection.

• More accuracy: higher recall, lower false positives, robust against glare, rain, and dirt.

• Safe to share: datasets carry no personal information, so they cross borders freely.

Synthetic visual and physical data doesn’t replace real-world testing—it supercharges it. By filling the gaps and covering every edge case, it gives automotive AI the confidence to move from the lab to the line, and from the factory floor to the insurance app.

At Datadoo, our mission is simple: engineer privacy, scale edge cases, and close the sim-to-real gap. For the automotive industry, that means safer cars, faster claims, and less waste.

Want to see how synthetic data can help your production line or insurance platform?