A 60-second anonymous demo of ORCA on a public corpus. No upload, no signup, no data leaves the demo environment.
No scripts to follow, no slides to sit through. You'll see the loop — Classify, Certify, Audit — running on a real corpus you can poke at.
Choose one of the pre-seeded issue codes — responsiveness, privilege, a sample regulatory issue.
ORCA surfaces the highest-information documents next. You label a handful; the model converges in minutes.
Pick a recall target. The cert engine tells you the moment you've statistically hit it — with a lower-confidence bound, not a point estimate.
Download a sample TAR Disclosure Package — the artifact you'd hand to opposing counsel on a real matter.
Three guided routes through the demo, depending on what you came to see. Pick one, or wander.
Walk through what a contract reviewer does: label 20 documents, watch the classifier learn, see your recall climb to 90%.
Skip the reviewer UI. See the statistical certification interface — when ORCA tells you "you've hit 85% recall, you can stop."
See the production output: TAR Disclosure Package, privilege log, Bates-stamped sample. The artifacts that defend the AI in a 26(f) report.
From a quick poke to a real pilot — pick the one that matches how much time you have.
No signup. No upload. Throwaway session. See what defensible-by-construction looks like running on real documents.
Launch demo →