Tinfoil
Verifiably private AI via hardware secure enclaves
Tinfoil is a practical choice for teams that need verifiable privacy in AI workloads, combining hardware enclaves with an easy-to-use Docker container service. The ~10% performance overhead is a fair trade for cryptographic proof of data isolation. Skip it if you don't need attestation or are on a tight budget—standard AI chat services are cheaper.
Verified 2d ago · liveness 76/100 · cite: rightaichoice.com/tools/tinfoil
- Developers building AI applications that require verifiable privacy
- Enterprises needing SOC 2/GDPR compliance for AI inference
- Researchers auditing frontier model weights without exposure
- Teams running sensitive Dockerized AI workloads in multi-tenant cloud
- Users wanting a free conversational AI with no privacy overhead
- Projects sensitive to ~10% performance overhead on inference
- Non-technical users who can't configure attestation and Docker
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Skip Tinfoil if you don't need cryptographic attestation or verifiable privacy, are on a tight budget, or can't handle the ~10% performance overhead—standard AI services are cheaper and faster.
The Private Chat plan has a fair-use policy and may be throttled during peak demand, potentially slowing your usage.
Tinfoil's $20/mo Chat plan is comparable to standard AI assistants like ChatGPT Plus, but with the added value of verifiable privacy. For teams needing attestation, the price is justified. Compared to self-hosting, Tinfoil saves setup and infrastructure costs, making it attractive for mid-size companies.
In short
Tinfoil — Verifiably private AI via hardware secure enclaves. Best for Developers building AI applications that require verifiable privacy, Enterprises needing SOC 2/GDPR compliance for AI inference, Researchers auditing frontier model weights without exposure. Free to start; paid plans from $20/mo.
What's new in Tinfoil
Checked 2 days agoAcross the latest 5 updates: 1 feature update, 1 launch and 3 news mentions.
Architecting secure prompt caching
Tinfoil implemented prompt caching for the Inference API using client-side cache secrets, preserving privacy.
NVIDIA Confidential Computing overhead benchmarks
First public benchmarks of confidential computing overhead on NVIDIA Blackwell for inference and training.
Towards Search, Memory, and More
Tinfoil Chat will get semantic search and cross-chat memory, built with privacy-preserving infrastructure.
Auditing a Frontier Model Without Seeing its Weights
Pour Demain ran gray-box interpretability evals on a 744B model inside confidential enclaves via Tinfoil Containers.
Introducing Tinfoil Containers
Tinfoil Containers enables deploying app backends, training pipelines, or proprietary models with verifiable privacy.
What people actually say about Tinfoil — is it worth it?
We ran a structured research pass across product reviews, community discussions, and post-purchase forum threads to surface the patterns vendors won't publish themselves. Below: the recurring strengths, the hidden costs people mention most, and the cohort that consistently regrets adopting this tool.
78 mentions across 5 sources (Hacker News, YouTube, Product Hunt, App Store, Lemmy) · researched Aug 11, 2026.
- +Cryptographic attestation gives real, verifiable privacy guarantees.
- +OpenAI-compatible API makes integration easy and drop-in.
- +Private Chat with end-to-end encryption and multi-device sync.
- +Runs on NVIDIA Blackwell with under 10% performance overhead.
- +Supports powerful open-source models like Kimi, unlike local AI.
- −Free trial restricts questions to 6-8, far too limited.
- −Privacy model may not withstand firmware-level attacks.
- −No independent long-term reliability data yet.
- −Name and branding may deter mainstream users.
- −Support response times unknown, community is thin.
- • Usage-based pricing for API and Containers could escalate quickly for high-volume workloads.
Viability Score
How well maintained and how widely used is Tinfoil? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: September 2026
How we score →Key Features
- Hardware secure enclave (TEE) execution on NVIDIA Blackwell GPUs
- Cryptographic attestation of code and model integrity
- Open-source attestation SDK for verification
- Browser-native verification with Sigstore and TUF
- Private Chat with end-to-end encrypted conversations
- Private Inference API (OpenAI-compatible) for AI apps
- Tinfoil Containers: run any Docker image in a TEE
- Multi-GPU support for large models
- Private web search with zero query visibility
- Encrypted chat backups and multi-device sync
- Speech-to-text input for chat
- Document upload for analysis
- Semantic search across chat history (in development)
- Cross-chat memory infrastructure (in development)
- Prompt caching with client-side secrets (recently added)
About Tinfoil
Tinfoil is a confidential computing platform that runs AI workloads inside hardware secure enclaves (TEEs) with cryptographic attestation. It's built for developers, enterprises, and researchers who need provable data privacy—not just promises. The platform offers three core products: Private Chat, a privacy-focused assistant available on web and iOS; Private Inference API, an OpenAI-compatible, open-source endpoint; and Tinfoil Containers, which lets you run any Docker image inside a secure enclave. All workloads run on NVIDIA Blackwell GPUs with less than 10% performance overhead, and Tinfoil is SOC 2 compliant, producing cryptographic proof that data never leaves the enclave. Tinfoil's key distinction is verifiability: it provides open-source attestation SDKs, browser-native verification with Sigstore and TUF, and private observability, so you can cryptographically confirm what code ran and that your data wasn't accessed. For Private Chat, features include end-to-end encrypted conversations, syncing across devices, speech-to-text, document upload, and a private web search that never reveals your queries. The platform also supports prompt caching with client-side secrets, which was recently added (July 2026), and is building semantic search and cross-chat memory, all with privacy at the core. Tinfoil is positioned for those who need cloud convenience without compromising on data ownership. Whether you're a researcher auditing frontier models, an enterprise handling sensitive data, or a developer deploying custom AI workloads, Tinfoil offers a unique blend of zero trust and ease of use—far simpler than self-hosting local AI, but with the privacy guarantees you'd expect from local execution. Compared to typical AI providers that rely on closed-source trust, Tinfoil gives you the power of cloud AI with hardware-enforced privacy, making it an ideal choice for regulated industries and privacy-conscious teams.
Behind the Verdict
Tinfoil stands out in the crowded AI privacy space by making verifiable privacy a core feature, not an afterthought. Its use of hardware secure enclaves (TEEs) on NVIDIA Blackwell GPUs provides cryptographic proof that data never leaves the enclave, which is a differentiator for regulated industries and researchers. The platform's three products—Private Chat, Private Inference API, and Tinfoil Containers—cover a range of use cases, from consumer chat to custom AI workloads. Strengths: Tinfoil's key strength is verifiability. It offers open-source attestation SDKs, browser-native verification with Sigstore and TUF, and private observability. This means you can cryptographically confirm what code ran and that your data wasn't accessed. The Private Inference API is OpenAI-compatible, making it easy to integrate with existing apps, and Tinfoil Containers lets you run any Docker image in a secure enclave, which is a major unlock for custom workloads. Recent updates include client-side prompt caching (July 2026) and plans for semantic search and cross-chat memory, which will enhance the Chat product. Weaknesses: The ~10% performance overhead on inference and training may be a dealbreaker for latency-sensitive applications. Setup requires technical expertise in Docker and attestation, so non-technical users may struggle. The Free tier is limited in tokens, and the $20/month for Chat plus usage fees for Containers can add up. Also, some features like semantic search and cross-chat memory are still in development. Where it fits: Tinfoil is ideal for developers building AI applications that require verifiable privacy, enterprises needing SOC 2/GDPR compliance, researchers auditing frontier models, and teams running sensitive Dockerized workloads. It's a great fit for organizations that want zero trust without the complexity of self-hosting. Where it doesn't: It's not for users who just want a free conversational AI without privacy overhead, or projects that can't tolerate 10% performance overhead. Non-technical users who can't configure attestation and Docker, and budget-constrained individuals who don't need attestation, should look elsewhere.
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Real-world workflow fit
Concrete scenarios for the personas Tinfoil actually fits — and what changes day-one when you adopt it.
You need to process sensitive user data with an LLM while maintaining compliance. You sign up for the Private Inference API, get an API key, and use the OpenAI-compatible endpoint with the open-source SDK. You implement client-side prompt caching to optimize costs.
Outcome: Your app processes data with cryptographic attestation, proving to users that their data is never exposed. You have verifiable privacy and can pass audits.
You need to run interpretability evals on a large model without seeing its weights. You use Tinfoil Containers to deploy the evaluation in a secure enclave, with the model provider bringing the weights and you bringing the evals.
Outcome: Both parties get cryptographic proof of exactly what ran, without exposing the weights. You publish your findings with confidence.
Your company needs to use AI on customer data under GDPR. You deploy a private chat for internal teams using Private Chat, ensuring conversations are encrypted and attestation is available for auditors.
Outcome: Your team uses AI while maintaining compliance. You can prove to regulators that data is handled securely.
Use Cases
- Deploy a private ChatGPT alternative for internal company use with verifiable data handling.
- Build an AI application that processes customer data under HIPAA/GDPR using enclave attestation.
- Audit a frontier model's behavior without exposing proprietary weights to the auditor.
- Run sensitive data analytics pipelines in a secure enclave with cryptographic proof of integrity.
- Fine-tune a model on confidential datasets using Tinfoil Containers and private post-training infrastructure.
- Use with coding agents and other third-party clients for private code generation.
- Run serverless enclaves for custom applications with the Python SDK.
Models Under the Hood
as of 2026-09-01
Limitations
- The Private Chat plan includes a fair-use policy and usage may be throttled during peak demand; it has a limit of 3 million tokens per hour.
- Tinfoil Containers pricing includes a monthly base fee plus usage charges.
- Setup requires technical expertise in Docker and attestation.
as of 2026-08-31
Verification history
We have re-verified Tinfoil 5 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
Free to cite with attribution — this page re-verifies continuously.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Plans compared
For each published Tinfoil tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Free
$0/mo
Ideal for
Individuals or developers exploring Tinfoil's capabilities without committing to a paid plan, with limited tokens to test the waters.
What this tier adds
Starting tier with access to Private Chat with limited tokens and limited API usage; no additional features.
Private Chat
$20/mo
Ideal for
Privacy-conscious users who want a powerful AI assistant with features like web search and document upload, and need to keep conversations private.
What this tier adds
Adds up to 3M tokens/hour, projects, web search, sync across devices, speech-to-text, document upload, and multi-modal AI compared to Free.
Private Inference API
Usage-based
Ideal for
Developers building AI applications that require verifiable privacy and need an OpenAI-compatible, usage-based API with attestation.
What this tier adds
Usage-based pricing with OpenAI-compatible endpoint, open-source SDK, cryptographic attestation, and client-side prompt caching—not included in Free or Chat.
Tinfoil Containers
$20/mo + usage
Ideal for
Teams running custom AI workloads or Dockerized applications that need verifiable privacy and the ability to run any image in a secure enclave.
What this tier adds
Adds the ability to run any Docker image in a TEE, with $20/month base fee plus usage, and includes attestation SDK and multi-GPU support.
Enterprise
Contact
Ideal for
Large organizations requiring custom compliance, SLAs, dedicated support, and on-premises deployment options for regulated workloads.
What this tier adds
Custom pricing with dedicated support, compliance and SLAs, and on-premises deployment—building on Containers with enterprise-grade services.
Where the pricing makes sense
The company stage and team size where Tinfoil's pricing actually pencils out — and where peers do it cheaper.
Tinfoil's $20/mo Chat plan is comparable to standard AI assistants like ChatGPT Plus, but with the added value of verifiable privacy. For teams needing attestation, the price is justified. Compared to self-hosting, Tinfoil saves setup and infrastructure costs, making it attractive for mid-size companies.
Setup time & first value
How long it actually takes to get something useful out of Tinfoil — broken out by persona, not the marketing-page minute.
For the Private Inference API, you can get an API key and start making calls in under 5 minutes. For Private Chat, sign up and start chatting immediately. For Tinfoil Containers, expect 20-30 minutes to deploy your first Docker image, as per the case study.
Switching to or from Tinfoil
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From [Other AI providers like OpenAI]: Switch your API calls to the OpenAI-compatible endpoint and use the Tinfoil SDK for attestation. No major code changes needed.
- ↗To [Standard AI providers like OpenAI]: If you decide to leave, you can migrate your chat history (export) and adapt your code to OpenAI's API since Tinfoil is OpenAI-compatible.
Integrations
Resources & Guides
Tutorials & Learning
Official links
Tools that pair well with Tinfoil
Common stack mates teams adopt alongside Tinfoil, with the specific reason each pairing earns its keep.
Featured Head-to-Head Comparisons
Tinfoil vs Audioeye
Tinfoil and AudioEye serve completely different needs: Tinfoil is for privacy-preserving AI workloads inside hardware enclaves, while AudioEye is for web accessibility compliance. Choose Tinfoil if you need verifiable data privacy for AI inference; choose AudioEye if you need ADA/WCAG compliance tools. There is no direct competition between them.
Tinfoil vs Push Security
These tools serve entirely different purposes: Tinfoil secures AI workloads inside hardware enclaves, while Push Security protects browsers from AI-driven attacks and data leaks. Choose Tinfoil if you need verifiably private AI execution for sensitive data. Choose Push Security if you must stop phishing, session hijacking, or LLM data leakage across browsers.
Tinfoil vs Temporal Ai
If your priority is absolute data confidentiality with cryptographic proof, choose Tinfoil – it runs AI inside secure enclaves with attestation. If you need to build reliable, fault-tolerant AI agents that survive crashes and retries, go with Temporal – its durable execution is the industry standard for workflow orchestration.
Alloy vs Tinfoil
Tinfoil and Alloy serve entirely different needs. Choose Tinfoil if you're a developer or enterprise that needs verifiable, attestation-backed privacy for AI inference, custom models, or sensitive data processing—and you're willing to accept ~10% overhead. Choose Alloy if you're a regulated financial institution that needs a unified, vendor-agnostic platform for fraud detection, AML, and onboarding orchestration across 270+ data sources. There's no overlap: one is about cryptographic privacy in AI, the other about compliance orchestration for finance.
Alternatives to Tinfoil
View all
Push Security
Browser-native security that stops AI-driven attacks and secures employee AI usage
Blackbox AI
Secure high-speed enterprise inference API for coding agents, zero data retention.
DuckDuckGo, optional Duck.ai
Private search engine and anonymous AI chat from DuckDuckGo
Frequently Asked Questions
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