Private
Intelligence

We build verifiably private AI so that you can trust the hardware, not the pinky-promises.

Our products

For your private thoughts, projects, and apps.

For your thoughts

Private Chat

Chat with powerful AI assistants while keeping your conversations private. Available in the browser and on iOS.

For your projects

Private Inference API

Build AI applications that keep all data private. Our API is OpenAI-compatible, open-source, and fully verifiable.

Usage-based pricing

For your applications

Tinfoil Containers

Run any Docker image in a secure enclave. Bring privacy and verifiability to applications and custom AI workloads.

$20/month + usage

Industry highlights.

Tinfoil in case studies, research, and collaborations.

Meta

Featured in a Llama case study as the only multi-GPU infrastructure offering production-ready, verifiably private AI.

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Red Hat

Collaborating with Red Hat on open-source confidential AI infrastructure for private inference.

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Trail of Bits

Security audit and webinar collaboration on TEE vulnerabilities and confidential computing best practices.

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Canonical

Our story on building audit-ready, verifiably private AI with Ubuntu as the foundation for multi-platform confidential computing.

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Industry Programs and Collaborations

NVIDIAMITIntel LiftoffCloudflare WorkersMeta LlamaConfidential Computing Consortium

Infrastructure built for privacy.

Tinfoil makes your AI workloads secure, verifiable, and private.

UC Berkeley
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!
Darya Kaviani, UC Berkeley
The Open Anonymity Project
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.
Erik Chi, The Open Anonymity Project
Workshop Labs
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.
Rudolf Laine, Workshop Labs

Privacy of local.
Power of cloud.

Tinfoil runs AI models inside secure hardware enclaves. This gives you the privacy of local AI with the power of cloud computing.

Tinfoil

Open-source & Custom Models

  • Provable Zero Data Retention
  • Cloud Convenience
    • LowSetup costs
    • LowComplexity
    • GoodScalability
  • Zero Trust
  • Private Observability

Frequently Asked Questions

Have a security or privacy question?

Detailed answers on what Tinfoil can and cannot see, how secure enclave attestation works, what would happened with legally-compelled disclosure, and more.

Security and Privacy FAQ

How does Tinfoil protect my data?

What does end-to-end privacy mean?

How is Tinfoil different from typical AI security approaches?

Is there a performance overhead when using Tinfoil?

Is Tinfoil compatible with closed-source models like GPT-5 and Claude?

What analytics and observability does Tinfoil offer?

Can I deploy my own AI models?

What type of workloads are suitable for Tinfoil?

Can I use Tinfoil with coding agents and other third-party clients?

Can I integrate Tinfoil with my existing application?

Can I keep server-side data and state?

Will Tinfoil eventually consider using fully homomorphic encryption?

Our Mission

Tinfoil was founded to create the private garden for thought.

As AI becomes more personal, omnipresent, and powerful, protecting the privacy of our conversations, thoughts, memories, and intellectual property is what preserves human relevance. AI should be an exoskeleton that empowers humans rather than replaces them. We are building the technical privacy safeguards to make this possible, using encryption, secure hardware, and other means to make it impossible for third parties to access your brain: a prerequisite for human empowerment and flourishing.