About Datanoc
We build synthetic datasets with simulation and generative AI. Our customers train and test vision models for manufacturing and robotics without waiting on real data collection.
Synthetic data for vision teams.
Real data is slow, expensive, and rarely covers the edge cases. We generate the data instead. Photorealistic simulation for physics and geometry. Generative models for texture and variation. Both delivered ready for your training pipeline.
Vision models for industry
We focus on inspection and robotics. The cases where missed detections cost time, money, or safety.
Simulation and generative AI
Photorealistic virtual stations and image generation models. Two methods that cover different gaps in real data.
Built for the Nordics
We work with suppliers, robotics companies, machine builders, and research groups across the region.
Data is the bottleneck.
Models are fragile. Development cycles are slow. Deployment risk is high. The cause is almost always the same.
Real data is hard to collect
Production lines and robot cells are busy. Pulling time for data collection competes with output.
Labeling is expensive
Pixel accurate labels are done by hand. Backlogs grow faster than teams clear them.
Edge cases are rare
The defects and scenarios that matter most are the ones the line produces least often.
Iteration is slow
Every change needs new data, new labels, and new line time. Cycles stretch into months.
Simulation and generative AI.
Photorealistic simulation
Virtual environments built to match the real one. Lights, cameras, materials, and defects are parameters. Labels come for free with each render.
Generative augmentation
Image generation models take a few real samples and produce controlled variations. Useful where simulation is hard and texture matters.
Pipeline ready
Datasets integrate into existing ML pipelines. Faster training, validation, and iteration without changing the stack.
Working with teams across the Nordics.
Small to medium sized suppliers, robotics companies, machine builders, and research groups. Teams building automated inspection stations, robotics perception systems, and AI driven applications.
What teams get out of it.
Faster time to a working model
Move data collection off the line and into software.
Coverage real data cannot reach
Rare defects, lighting variation, and angles modeled at the volume training needs.
Lower cost per iteration
Regenerate the dataset when conditions change. Same pipeline.
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.