Tinfoil Blog

How we replaced general-purpose firmware with code built exactly for our machines, moving its complexity out of runtime and into measured build artifacts and significantly reducing the size of the trusted code base.

Our approach to safeguards in Tinfoil Chat that keeps your conversations private: model evaluations before hosting, plus safeguard models that run exclusively inside secure enclaves.

How Tinfoil implemented prompt caching for the Inference API without compromising on privacy, using client-side cache secrets.

The first public benchmarks of confidential computing overhead on NVIDIA Blackwell for inference and training.

A look at the infrastructure groundwork behind two features coming to Tinfoil Chat: semantic search across your history and cross-chat memory that does not compromise on privacy.

How Pour Demain used Tinfoil Containers to run gray-box interpretability evals on a 744B parameter model inside confidential enclaves, without exposing the weights.

How Tinfoil thinks about supply chain security for client-side code and build infrastructure.

Tinfoil Containers lets you deploy your application backend, your training pipeline, or your proprietary model on Tinfoil and build end-to-end verifiably private AI services.

How we cryptographically guarantee that we are serving specific, untampered model weights that clients can verify on each request.

How we built shareable conversation links while preserving conversation privacy.

A look into our system design, threat model, and evaluation for private web search—architected so that even Tinfoil cannot see your search queries.

Learn how we built a browser-based confidentiality and integrity verifier with implementations of browser-native Sigstore and TUF libraries.

Introducing encrypted chat backups and multi-device syncing that extends our end-to-end privacy principles to persistent cloud storage.

Fully private coding with qwen3-coder-480b.

Sam Altman announced OpenAI is considering encrypted chats for ChatGPT. We explore the technical challenges and why true privacy might require OpenAI to actually be "open".

OpenAI just released gpt-oss-120b. We just made it available on Tinfoil with verifiable privacy guarantees.

An in-depth comparison of AI privacy solutions that explains why secure enclaves offer the best balance of privacy and performance for AI applications today.

A deep dive into side channel attacks, why they matter for AI security, and how Tinfoil provides defenses against these sophisticated threats.

Learn how Tinfoil compares to Oblivious HTTP (OHTTP) and what the right solution is for AI applications requiring data privacy.

Learn how Tinfoil reduces complexity to provide better transparency and security.

Try out Tinfoil Chat with DeepSeek R1.

Learn how Tinfoil compares to other confidential computing platforms in terms of security and usability.

Learn how Tinfoil builds trust through code transparency, automated builds, transparency logs, and automated code attestation.

Learn how Tinfoil provide confidential computing with hardware-level isolation, integrity verification, and code transparency.

Discover how Tinfoil enables verifiably private AI deployment using secure hardware enclaves, extending local security boundaries to the cloud.