Behavior
Human task sequences.
Study how real people reach, pause, hand off, recover, share workspaces, and move through cluttered spaces.
Researchers
Build on physical-world data that cannot be scraped.
TRACE is opening an early researcher path for embodied AI teams that need synchronized motion, scene context, timing, and cooperation from ordinary work outside the lab.
Research pipeline
Early harvest tooling is designed to move synchronized sessions into validated dataset inventory.
WELL
data corpus
Governed real-world human task sessions for embodied AI.
Multi
modal streams
Motion, scene, timing, audio, and task context captured together.
Early
access path
Built for fit-first research and pre-revenue exploration.
License
deployment
Commercial use requires terms that protect the dataset and contributors.
The data
A useful robotics corpus has to preserve the body.
Language datasets preserve words. Vision datasets preserve pixels. Robotics datasets need the coupled record of movement, environment, task progress, and human timing.
Context
Scene and motion together.
Pair first-person scene data with body-worn motion streams so policy work can connect intent, environment, and movement.
Scale
Outside the lab.
The research value comes from ordinary settings that mocap studios and staged demos rarely capture well.
Research areas
The first use cases are practical, physical, and cooperative.
The WELL is most valuable where robots need to work around people, tools, space, and changing context rather than clean benchmark scenes.
Capture hardware
The MMT core anchors scene and task capture while body sensors add motion fidelity.
Policy pretraining
Imitation learning
Human-aware navigation
Manipulation priors
Cooperative task modeling
Dataset mixture studies
Embodied evaluation
Safety and proximity research
Access path
Research access starts with fit, not a generic download.
TRACE matches access to the work being done. That keeps early research useful while respecting contributor accounting, consent boundaries, and deployment licensing.
Person
Sensor kit
App
The WELL
Behavior models
Every uploaded hour moves through quality grading, fraud detection, consent-aware capture settings, and contributor accounting before it can enter the WELL.
01
Request research access.
Share the research problem, task category, model type, and whether the work is academic, open, pre-revenue, or commercial.
02
Match the right data path.
TRACE can map early requests to exploratory data products while keeping deployment licensing separate.
03
Work inside clear terms.
Access should protect contributors, consent boundaries, privacy controls, and the long-term usefulness of the corpus.
Licensing
Open enough to learn. Structured enough to deploy.
The access model keeps research and commercial deployment distinct, so the WELL can support early discovery without giving away the economics of production use.
Research
Exploration should be easy to start.
Non-commercial research and pre-revenue work can use a lighter path where the goal is learning, evaluation, and publication rather than deployment.
Commercial
Deployment needs licensing.
When data contributes to a commercial model or product, licensing should support dataset operations and contributor-aligned economics.
Governance
Terms follow the data.
Different task categories may carry different quality grades, capture constraints, privacy boundaries, and downstream usage limits.
Questions
The research path should stay precise.
The goal is not to promise a magic robotics dataset. The goal is to build a practical, governed corpus that makes hard physical behavior easier to study.
Data format
Will the WELL be raw or labeled?
The intent is to preserve raw multimodal value while adding enough metadata, task structure, and quality grading to make research work practical.
Availability
How does access start?
Research access starts through the request flow. TRACE uses that intake to understand fit, task category, and the right access path as WELL inventory grows.
Synthetic data
Why not use simulation only?
Simulation can help, but robots still need the messy record of human physical behavior: timing, hesitation, tool use, proximity, and adaptation.
Research access
Start with the task data your team actually needs.
Tell TRACE what you are studying, which task categories matter, and whether the work is research-only, pre-revenue, or moving toward deployment.