Encrypted context, memory, and vector DB for every model and agent
Knowledge bases, vector stores, conversation history, agent memory. Every piece of context an AI reaches for is plaintext the moment it's loaded.
For enterprise SaaS
Ship AI features without seeing your customers' data.
Your customers want AI in your product. Their security review wants a guarantee you can't honour with plaintext access. Today most teams choose: skip the feature, or skip the deal.
FHE under your AI features. The promise you make to your customers, you can actually keep.
Use cases for this audience
5 scenarios
Fine-tune on customer data without ever seeing it
Domain models need real customer data to be useful. Training in plaintext means you hold what you swore you wouldn't.
Answer security questionnaires with evidence, not adjectives
Sales cycles stall on 400-row spreadsheets your team rewrites by hand every quarter.
Let AI review code that never leaves your machine
To use an AI code tool you usually hand it your source, secrets, and proprietary logic. And trust a retention promise.
Stop your model from being cloned out the back door
Distillation attacks turn your API into someone else's competing model in weeks.
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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.