Tinfoil ⋅ Confidential AI

Features

Security you can verify

GitHub

Sigstore

Commit

a1b2c3d4e5f...

Commit

f6e5d4c3b2...

Commit

e45c91f4d1c...

Enclave code

e45c91f4d1c...

Match!

Security

Hardware-Enforced Security

Run AI workloads with hardware-backed security through secure enclaves and cryptographically-verifiable runtime attestation. Your data stays encrypted end-to-end by hardware-level safeguards and cannot be accessed by anyone other than you — not even Tinfoil or the cloud provider.

Performance

Bare-Metal Performance

Powered by NVIDIA Hopper and Blackwell architectures, Tinfoil delivers confidential computing with near-identical performance to unencrypted workloads — even for the largest AI models.

Deployment

Cloud-Native Deployment

Get an on-prem level of security with the convenience of cloud deployments. We manage the infrastructure while you maintain complete control over your data.

Privacy Preserving

Observability

Privacy-Preserving Analytics

Monitor and debug your applications with Prometheus compatible metrics that give you rich analytics and insights — all with end-to-end privacy through industry-standard secure aggregation protocols. Keep using the tools and workflows you love, while we handle the privacy-preserving aggregation behind the scenes.

Experience Tinfoil in action

Use Confidential AI

Tinfoil Chat

Confidential chat with DeepSeek R1:

•Only you can see your conversations
•In-browser security verification

Try our private chat

Tinfoil Inference API

Integrate confidential AI in your products:

•All API calls are completely private
•Verifiable integrity and confidentiality

Find out more

FEATURE COMPARISON

On-Prem Security with the Convenience of Cloud

Feature comparison
DATA PROTECTION
	OpenAI	On-Prem	Tinfoil
Data never leaves your control	Not included in OpenAI	Included in On-Prem	Included in Tinfoil
FEATURES
Cloud‑native deployment	Included in OpenAI	Not included in On-Prem	Included in Tinfoil
Privacy-preserving observability	Not included in OpenAI	Not included in On-Prem	Included in Tinfoil

Use Cases

From personal projects to enterprise solutions, we can help you secure your AI workflows.

Personal

Interact freely with AI assistants, knowing that no one in the world except you can see your conversations.

Private Chat

Privately chat with AI assistants about mental health, personal finance, and other sensitive topics, knowing that no one except you can read your messages.

Private Data Analysis

Analyze sensitive financial or health data privately.

Enterprise

Enable secure collaboration and compliance at scale.

AI Code Assistants for Proprietary Code

Empower employees to use AI code assistants without being concerned about proprietary code and documents being exposed to third parties, without having to run a model on-prem.

Maintain Competitive Advantage

Take advantage of the latest AI technologies such as AI code assistants, AI chat, and AI knowledge discovery, without exposing your proprietary code and documents to external parties.

For Cloud Providers

As a cloud provider, you can offer your customers the ability to run a proprietary model or work with sensitive data without having to trust your platform.

Startups

Give customers the confidence to fully embrace your AI products by guaranteeing that their sensitive information is never revealed to anyone.

AI applications that integrate private data

Remove the privacy barrier that stops users from fully embracing your AI products.

Private Content Moderation

Run AI content moderation that your users can trust and verify.

Enterprise-Ready Security

Make your products ready for enterprise customers.

Frequently Asked Questions

• Tinfoil uses secure enclaves with hardware-backed cryptographic guarantees. It uses a combination of technologies like AWS Nitro Enclaves for CPU-only workloads and AMD SEV with NVIDIA confidential computing enabled GPUs for larger workloads.

• To provide verifiability, we use Sigstore as our transparency log which makes the confidentiality claims publicly auditable.

Your data is encrypted directly to the enclave, no one can access it but you and the model that lives inside the enclave. Even Tinfoil cannot see your conversations.

Most AI security relies on access controls, where you have to trust the provider to handle your data appropriately. In contrast, solutions like Apple's Private Cloud Compute demonstrate true hardware-backed security but remain limited to Apple's ecosystem. Tinfoil uses secure enclaves and hardware-level isolation to provide the same level of security guarantees through verifiable hardware protections.

• For CPU-only workloads, the performance is identical to unencrypted workloads.

• For GPU workloads using NVIDIA Hopper series, there is a small performance overhead. See the NVIDIA blog for details on overheads.

• For NVIDIA Blackwell series, there is almost no difference in performance.

No. Tinfoil only supports open-source models like Llama and DeepSeek, or custom models provided by our customers.

Tinfoil provides Prometheus-compatible metrics with privacy-preserving analytics, allowing you to monitor and debug your applications while maintaining privacy through industry-standard secure aggregation protocols.

Yes! Tinfoil supports deployment of your own models.

Tinfoil supports a wide range of workloads, including inference, fine-tuning, and RAG applications. We are currently in private preview and are actively working with customers to support their specific use cases.

No, third-party tools use their APIs through which your data is sent. However, Tinfoil can be used with similar open-source tools.

Yes! Tinfoil supports the OpenAI Chat Completions APIstandard, making it easy to integrate with your existing application.

Enclaves are stateless between requests and do not have access to external storage. However, we do offer privacy-preserving analytics and observability for your workloads.

In short, FHE is not something that we believe will scale to support AI applications anywhere in the near future. Even with latest advancements in hardware-accelerated FHE, it is in no way sufficiently powerful to run large-scale AI workloads in real-time. Some companies have successfully deployed FHE for some limited use cases (e.g., blockchains and static database queries) where the performance overhead of FHE is less of a barrier. However, for anything moderately more powerful, all existing FHE approaches quickly hit a performance wall.

Confidential AI

Chat with confidential AI

Run your own AI workload

Features

Security you can verify

Security

Performance

Deployment

Observability

Experience Tinfoil in action

Use Confidential AI

Tinfoil Chat

Tinfoil Inference API

FEATURE COMPARISON

Use Cases

Personal

Private Chat

Private Data Analysis

Enterprise

AI Code Assistants for Proprietary Code

Maintain Competitive Advantage

For Cloud Providers

Startups

AI applications that integrate private data

Private Content Moderation

Enterprise-Ready Security

Frequently Asked Questions

How does Tinfoil protect my data?

What does end-to-end encryption mean?

How is Tinfoil different from typical AI security approaches?

Is there a performance penalty?

Is Tinfoil compatible with closed-source models like GPT-4 and Claude?

What analytics and observability does Tinfoil offer?

Can I deploy my own AI models?

What type of workloads are suitable for Tinfoil?

Is Tinfoil compatible with tools like Perplexity and Copilot?

Can I integrate Tinfoil with my existing application?

Can I keep server-side data and state?

Will Tinfoil eventually consider using fully homomorphic encryption?

Ready to see Tinfoil in action?

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