Bring in the work
Start with the files, cases, or batches your team already uses. No demo-only workflow.
→Detection is cheap. The reviewed decision is the product. Start from an open model, sign the hard call as the work happens, and keep the evidence and the weights.
Detection is cheap. What survives examination is the signed decision behind it.
Each failure enters a regression bank, so the same mistake never ships twice.
A pilot reviews 100 to 500 episodes for $25K to $100K, and leaves you a model you own.
Bring the work. Standardize the step nobody trusts. Route it to the expert, sign the evidence, improve the model, keep the weights.
Start with the files, cases, or batches your team already uses. No demo-only workflow.
→Failed case routes to a reviewer. The hard call gets a policy finding, a regression gate, and a release hold. You leave with a signed evidence packet.
→The next team gets a decision that survives examination. The model improves on your approvals. Your team keeps the weights.
Building in-house means starting from scratch. Renting an endpoint means you improve a model you never get to keep. App Data OS runs in your tenant and leaves the tuned model with your team.
Every app runs in your VPC, on your keys, under your retention policy. HIPAA, SOC 2, audit-ready.
A managed endpoint rents you the intelligence; you walk away with nothing. Here the tuned model stays with your team on export, forever.
Human Data OS routes the hard case to the right expert. Those approvals and corrections are the signal that improves your model.
Eighteen wedges into one loop. Each card: the app, the open model it starts from, what it does, and the result you keep.
The two we lead with. Models scores runs, holds regressions, and governs releases for teams building models. Robotics reviews episodes and exports rights-cleared training manifests for teams training robots.
Score the runs, hold every regression, train, govern releases, and keep the weights.
Review episodes, score safety, check dataset quality, and export training manifests.
Generate the data you can't collect, and keep spatial and 3D work traceable from capture through handoff.
Generate governed datasets, or simulate cohorts to test a decision before it ships.
Keep scene, alignment, and delivery decisions traceable from capture through handoff.
Screen sequences, compare routes, and keep every hard clinical decision attached to the record behind it.
Screen risky sequences before they reach synthesis or the bench.
Compare routes and choose the path the bench can actually defend and run.
Scout assets, review evidence, map trials, and keep diligence packets on one record.
Keep cohort and variant findings attached to the evidence that supports them.
Triage cases and keep every hard clinical decision attached to the record behind it.
Review scans, escalate ambiguous studies, and export study-ready packets.
Check simulations against reality, screen material candidates, sort signal from noise, and ground a reporting record people can trust.
Review simulations against reality before a result moves into design, science, or reporting.
Screen material candidates and move only the right ones into qualification.
Separate real signal from noise before scarce follow-up time gets spent.
Turn climate scenarios and monitoring work into a reporting record people can trust.
Review site conditions and document which response was actually approved.
Review risk decisions, inspect production issues, and check changes against requirements before they ship.
Review risk decisions and explain the edge cases before an examiner or committee asks.
Review inspections and decide what can ship with the evidence attached.
Review changes against requirements before they become release, safety, or cost problems.
Begin from an open model already suited to the work. Sign the reviewed decision as it happens. Keep the tuned weights, ahead of the EU AI Act clock.
Every app begins from an open model already suited to the work, not a blank slate.
Provenance, the reviewer's rationale, and a signed packet as the work happens. The kind of record the EU AI Act high-risk provenance deadline expects in August 2026.
Approvals and corrections from real cases tune your model. The stronger result stays with your team on export.
Bring the work. Keep the proof. Own the model. We'll map the workflow, pick the open model, sign the hard call, and leave you the weights. A robotics pilot reviews 100 to 500 episodes for $25K to $100K.
An open model already suited to your field.
A signed evidence packet, a reviewed record, and weights you keep.