Know which attacks your AI would actually survive
A point-in-time pentest is stale the week after it's filed. New jailbreaks land daily.
For system integrators
A Mirror practice for regulated AI deployments.
Your enterprise clients want AI; their compliance teams want guarantees no off-the-shelf model can give. Each engagement is a custom build that delivers value once and rebuilds the next time.
Mirror as the reusable platform your delivery team implements. Same primitives, every engagement.
Use cases for this audience
5 scenarios
Show the auditor what your AI did, and why
"Trust us, we logged it" doesn't pass a regulator anymore. You need signed, tamper-evident proof for every decision.
Answer security questionnaires with evidence, not adjectives
Sales cycles stall on 400-row spreadsheets your team rewrites by hand every quarter.
Run AI inside an air-gapped or sovereign boundary
Defence, government, and regulated workloads can't legally move data outside their boundary. So they're locked out of AI entirely.
Catch the risk before launch, block it in production
Pre-prod findings die in a Jira backlog. Runtime sees attacks the red team never imagined.
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See encrypted AI security in action.
FHE-native inference. Runtime agent guardrails. Continuous red teaming. One platform. Book a working session with the team.