Synthetic data for
production AI systems
From autonomous vehicles to medical imaging, datadoo generates the training data your models need.
Autonomous Vehicles
Physics-accurate simulation of every road condition, weather pattern, and edge case. Generate millions of driving scenarios with realistic sensor outputs - without putting a single car on the road.
- Any weather, lighting, and road condition on demand
- Rare edge cases impossible to capture safely
- Multi-sensor simulation (camera, LiDAR, radar) with synchronized outputs
- Datasets ready for regulatory validation
Robotics & Physical AI
Physics-accurate environments for sim-to-real transfer. Generate training data where gravity, friction, and collisions behave exactly as they do in the real world.
- Physics-accurate environments
- Manipulation & grasping scenarios
- Warehouse and industrial settings
- Sim-to-real transfer optimization
Medical Imaging
Privacy-safe medical training data. No patient consent required, full regulatory compliance. Train diagnostic models without compromising patient privacy.
- HIPAA & GDPR compliant
- No patient data required
- Rare pathology generation
- Multi-modality support (X-ray, CT, MRI)
Insurance & Inspection
Damage detection trained entirely on synthetic data. Our GTC 2026 research shows windshield damage segmentation that issues repair-or-replace decisions insurers can audit - without a single real frame.
- Physically accurate glass, optics, and damage taxonomies
- Segmentation-grade labels for measurement and reporting
- 40% faster dataset generation (GTC 2026 research)
- Qualified repair vs. replace verdicts for claims teams
Object Detection
High-quality bounding boxes and segmentation masks across millions of synthetic objects. Perfect annotations every time, at any scale.
- Pixel-perfect annotations - zero label noise
- Export in any format (COCO, YOLO, VOC, custom)
- Infinite object variations with controlled diversity
- Occlusion, viewpoint, and scale diversity built in
Synthetic Imagery
Photoreal synthetic images with pixel-perfect annotations for any scenario. Control every aspect of the scene composition.
- Photoreal rendering quality
- Full scene control
- Consistent annotation quality
- Scalable to millions of images
Dataset Augmentation
Fill gaps in existing datasets. Boost underrepresented classes and edge cases. Improve model robustness with targeted synthetic data.
- Gap analysis for existing datasets
- Targeted class balancing
- Domain adaptation support
- Seamless integration with real data
Why datadoo
How we compare
See how datadoo stacks up against manual labeling and other synthetic data tools.
| Feature | datadoo | Manual labeling | Other tools |
|---|---|---|---|
| Annotation consistency | Automated, deterministic | Inter-annotator variance | Varies |
| Time to first dataset | Hours | Weeks | Days |
| Scale ceiling | Unlimited | Labor-limited | Platform-limited |
| Edge case coverage | On demand | If captured | Limited variation |
| Sim-to-real evidence | Scores + lineage per dataset | None | Rarely |
| Privacy compliance | Built-in | Manual audit | Varies |
Annotation consistency
- datadoo
- Automated, deterministic
- Manual labeling
- Inter-annotator variance
- Other tools
- Varies
Time to first dataset
- datadoo
- Hours
- Manual labeling
- Weeks
- Other tools
- Days
Scale ceiling
- datadoo
- Unlimited
- Manual labeling
- Labor-limited
- Other tools
- Platform-limited
Edge case coverage
- datadoo
- On demand
- Manual labeling
- If captured
- Other tools
- Limited variation
Sim-to-real evidence
- datadoo
- Scores + lineage per dataset
- Manual labeling
- None
- Other tools
- Rarely
Privacy compliance
- datadoo
- Built-in
- Manual labeling
- Manual audit
- Other tools
- Varies
Any domain. Any object. Any label.
These are just starting points. datadoo generates physics-accurate synthetic data for any visual domain. Tell us what you need.