Get the right people. Get the data only they can give.
For AI labs, robotics labs, and voice labs.
Anyone can ship a model. Few can prove it holds up. AuraOne gets you the people who make your data right — and the AI you own to keep it that way.
One brings you the people who make your data right. The other turns that work into AI you own.
For AI labs, robotics labs, and voice labs.
Eighteen applications. You keep the weights.
Programs at a frontier AI lab.
DirectionalReviewer pickup to sign-off, a regulated decisioning program.
DirectionalCaught at the gate across an enterprise rollout.
DirectionalTest the run. Review the hard cases. Recruit the right specialist. Remember the misses. Approve what's right.
Test the run.
Review the hard cases.
Recruit the right specialist.
Remember the misses.
Approve what's right.
Evidence accumulates as the record moves.
Each app starts from a proven open model, runs inside your work, and learns from your data. You keep the weights.
See every applicationScreen risky sequences before they reach synthesis or the bench.
Open appCompare routes and choose the path the bench can actually defend and run.
Open appReview simulations against reality before a result moves into design, science, or reporting.
Open appScreen material candidates and move only the right ones into qualification.
Open appSeparate real signal from noise before scarce follow-up time gets spent.
Open appTurn climate scenarios and monitoring work into a reporting record people can trust.
Open appReview site conditions and document which response was actually approved.
Open appTriage cases and keep every hard clinical decision attached to the record behind it.
Open appReview changes against requirements before they become release, safety, or cost problems.
Open appKeep scene, alignment, and delivery decisions traceable from capture through handoff.
Open appReview inspections and decide what can ship with the evidence attached.
Open appReview risk decisions and explain the edge cases before an examiner or committee asks.
Open appCollect the real-world human actions, spaces, tools, and failure cases robots need to learn.
Open app“Release review went from a three-week scramble to a repeatable gate. When an edge case slips, we catch it, we save it, and it never ships again.”