RGB video datasets for real‑world manipulation.
Captured in authentic workshops and production environments through trusted partners—designed around the behaviors and edge cases your model needs to learn.
How we work with partners on the ground
A short look at real annotation and review workflows, plus what processed output can look like—clear instructions, consistent rubrics, and quality checks so everyone knows what “good” looks like before data ships.
On-site workflow
How capture and review are run day to day with partners.
Annotated data example
Representative view of footage after labeling and QA—formats vary by your spec.
What you can request
Start with a pilot batch, validate model impact, then scale. We’ll help translate your training objective into a dataset spec that’s feasible and high-signal.
- Manipulation sequences with hands + objects in natural settings
- Single-camera or multi-camera capture setups
- Task labels and structured metadata when needed
- Annotation, labeling, and QA loops to keep consistency high
- Versioned dataset drops in agreed formats
Request a dataset
Share your target behavior and timeline. We’ll reply with a proposed spec and next steps.
Annotation and labeling that matches your training pipeline.
Beyond capture, we help teams turn raw footage into structured training data—using pragmatic specs, review loops, and iteration based on model feedback.