Tinfoil

We have fast deployment cycles for servers that we run on Tinfoil TEEs to guarantee customer privacy. Tinfoil Containers makes the TEE deployment friction almost nonexistent and lets us iterate quickly. It's an important step towards the future where most ML workloads are secured by running on verifiably-private TEEs.

When building The Open Anonymity Project at Stanford and UMich, we were using Azure's confidential containers (ACI) which is a nightmare to set up correctly, from TLS certificate binding, hardware measurements, reproducible image digests, etc. We can do the same thing on Tinfoil Containers in <20mins with the nice attestation SDK, clear docs, debug mode, almost zero update down time, and transparent architecture that everyone can audit.

Running our own custom Docker container on Tinfoil Containers is a major unlock. It lets us run our full end-to-end system in trusted hardware using the same simple Python SDK we already use to call Tinfoil's embedding and LLM models. Serverless enclaves have finally arrived!