End-to-end Encryption
Inbound data is encrypted client-side by the SDK before it passes through the gateway. Output is re-encrypted inside the TEE before it returns to the client.
Enterprise
Enclave runs AI inference on your most sensitive data inside confidential, attested hardware - encrypted in transit, at rest, and in use. Your data is never readable by anyone. Not even us.

Why Enclave AI
The client SDK verifies signed attestation evidence against the release manifest before data moves. Only then is the request sealed for the enclave and returned as an encrypted response.
Inbound data is encrypted client-side by the SDK before it passes through the gateway. Output is re-encrypted inside the TEE before it returns to the client.
Models run inside hardware-isolated secure enclaves. Memory is encrypted in use, with remote attestation you can verify.
Run any open-source model that fits your workload, then adapt it with LoRA adapters so inference can be tailored to your specific dataset and domain.
Connect CRM, notes, decks, docs, analytics and support tools in a click. Every connector is encrypted and least-privilege scoped.
Prompts, responses, and logs are encrypted and stored on the user's device by default. Optional encrypted cloud storage enables secure cross-device access.
Build your own applications with the Enclave SDK and OpenAPI-compatible interface, so private inference can live inside your own product workflows.
CONFIDENTIAL AI MODEL
Enterprise AI secured with end-to-end encryption and confidential computing, built for organizations operating under strict regulatory requirements.
OpenAI-compatible LLM endpoints with private prompts and verifiable runtime states - enabling secure deployment of your own custom Docker workloads.
Check allOpenAI
Gpt-oss
Alibaba
Qwen3
MoonShot
Kimi K3
Meta
Llama 3.3
Z.ai
GLM 5
FAQs
Still deciding whether Enclave fits your compliance posture? These are the questions teams usually ask first.
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