The robot did something surprising. What, exactly, was it running?
Teleop demos, fleet logs, sim rollouts, VLA fine-tunes — every policy you deploy is the product of a data mixture somebody curated and a recipe somebody remembers. roar records that recipe automatically, at runtime. GLaaS resolves any deployed checkpoint's hash back to the data, code, sim build, and environment that made it.
Four questions your team answers weekly. Now they're lookups.
Sim and real, one graph.
Sim rollouts carry the simulator's code, commit, and parameters in their lineage; teleop and fleet data are hashed at ingestion. Real and synthetic data live in the same graph, so mixture provenance is one hop — not a spreadsheet.
Deployed checkpoint → full recipe.
An incident review starts from the checkpoint's hash — not from
Slack archaeology. roar show <hash> returns the
data mixture, code, environment, and every upstream job. The
chain of custody survives the copy to the robot.
Membership is a hash query.
Composite artifacts treat a 5M-file dataset as one addressable node — with membership queries. "Was this episode in the training set?" gets a yes/no from the record, not a shrug.
Recipes that survive departures.
The curation decisions, mixture versions, and hyperparameters that produced your best policy are recorded as a byproduct of running the job. The team inherits the record, not a four-bullet handoff doc.
"We can't reproduce a model from three months ago. Would be great to have the recipe & datasets stashed."
— CTO, Series B robotics companyYour stack stays. One prefix changes.
That prefix is the entire adoption cost — for one researcher or the whole lab.
roar observes at the syscall level — if the job read it or wrote it, it's in the graph.
Evidence for the day someone asks.
Incident-ready by default.
When a deployed policy misbehaves, the investigation is a lineage walk — and when a customer, regulator, or safety review asks how a model was built, the answer is a generated document, not a quarter of archaeology.
- CycloneDX 1.7 AI-BOM from any registered lineage
- scored against G7 / CISA / NTIA guidance
- mapped to EU AI Act Annex IV
Your fleet data never leaves.
GLaaS stores the recipe, not the ingredients. Sensor logs, teleop sessions, checkpoints, and datasets stay in your buckets and on your infra — the registry holds hashes, commands, and graph edges, published under your private scope.
- secret values redacted before publish, with confirmation
- private-by-default for teams · export as open JSON
- self-hosted GLaaS on Enterprise
Try it on your next policy run.
Hand it to whoever trains next.
The fastest evaluation: one researcher, one training job, thirty seconds. Or talk to us about a pilot — we work with robotics teams from seed to Series B and beyond.
Point roar at your next run.
No account, no code changes. Works the same on a laptop fine-tune or a multi-node Ray job.