AI inference and web analytics often require processing sensitive user data in the cloud, raising significant privacy concerns. Traditional methods rely on trust in cloud providers, potentially exposing user queries, personal information, and proprietary data to unauthorized access. Compliance with data privacy regulations adds further complexity and cost.

Tinfoil provides a confidential computing platform that enables privacy-preserving AI inference and web analytics. By leveraging secure enclaves and cryptographic techniques, Tinfoil ensures that user data remains protected throughout the processing lifecycle. The platform allows users to interact with AI models and gain aggregate insights without exposing the underlying data, prompts, or conversations. Tinfoil's solutions are designed to integrate seamlessly into existing AI workflows, offering a balance between robust security and high performance. This approach allows organizations to maintain data sovereignty, comply with privacy regulations, and build trust with their users.

Hardware-backed security using trusted execution environments (TEEs) and runtime attestation

End-to-end encryption to protect data, prompts, and models

API-compatible integration for drop-in deployment with minimal code changes

Support for open-source and custom AI models, including DeepSeek, Llama, and Mistral

Private observability tools for aggregate telemetry data without compromising user privacy

Verifiable code transparency through open-source code and automated builds

SOC 2 Type I compliance

Support for NVIDIA Hopper and Blackwell architectures for bare-metal performance

Tinfoil targets enterprises, startups, and individual developers who require secure and private AI solutions, particularly those working with sensitive data in regulated industries.

Tinfoil offers a tiered pricing model, including a $20/month subscription for private chat, a pay-per-token model at $2 per 1M tokens for private inference, and custom pricing for business deployments with dedicated support.