Generate the data you can't collect.
We render the world your models need to see, fully labeled and ready to train, so data is never your bottleneck again.
Cover every scenario, every condition, at any scale.
Vision models are only as good as the data behind them.
For teams working on models, data collection is the main driver of project cost and timeline. It is also the reason deadlines slip.
Real data is hard to collect
Every production line is dynamic, complex, and unique. Test slots are competitive. Unlike public datasets, industrial data usually has to be captured from scratch.
Labeling is expensive
Each data sample needs careful annotation. Costs and timelines stack up before training even starts.
Edge cases are missing
Models are trained on the data that was easiest to collect. Rare but critical scenarios remain underrepresented and systems less reliable in production.
Live testing is hard to schedule
Testing on commissioned production lines is shared across suppliers, integrators, and internal teams. Test time is limited, heavily coordinated, and costly to secure.
Can you spot the synthetic one?
Let's see if you can tell the difference between a real photo and a synthetic one. These are the same kinds of images we show our models. They learn to recognize the defects and details that matter without ever knowing which ones were real.
Real or Synthetic
Spot the synthetic oneX-ray scan
Pick the one you think is synthetic.
How close is synthetic to real?
We do not just claim it looks right. We measure it. This is a comparison of real wallplug images against our synthetic ones, mapped into the same space and scored on how well the two image sets match.
Coverage scores lower than the other three because this sample has only 40 synthetic images against 80 real ones. Generating more images covers more of the real variety, and a dataset can include as many as a project needs.
Talk to us about your dataset.
Tell us the inspection task and the conditions. We will come back with what is feasible, the timeline, and the cost.