Tinfoil
Tinfoil runs private AI inference inside hardware secure enclaves so you can cryptographically attest which code and model handled your
Tinfoil is the pick when you need to prove to an auditor, a customer, or yourself that a specific model ran on your data and nobody else saw it. The attestation chain is the product, and the $20/month Chat plus usage-based API keep entry cheap enough to test before committing to containers. Skip it if you just want the lowest per-token chat bill and have nothing sensitive in the prompt.
Verified 5d ago · liveness 76/100 · cite: rightaichoice.com/tools/tinfoil
- Developers shipping AI features that need verifiable, API-level privacy rather than a data-processing promise
- Enterprises in defense, legal, and regulated sectors blocked from mainstream providers
- Researchers running gray-box interpretability evals on large open model weights
- Teams moving sensitive Dockerized AI workloads off local GPUs and into confidential cloud
- Shoppers optimizing purely for dollars per million tokens with no sensitive data
- Casual users who want a free conversational assistant without a privacy premium
- Latency-critical workloads where the sub-10% enclave overhead matters
We scan live Reddit threads, YouTube comments, X posts, G2 reviews and other communities — and hand you an honest verdict in under a minute.
- Honest verdict, not marketing
- Real pros & cons from real users
- Attributed quotes with receipts
3 free scans · no card needed
Skip Tinfoil if you only want the cheapest per-token conversational AI and neither the $20/month Private Chat nor enclave attestation solves a problem you actually have.
Private Chat's fair-use policy allows throttling during peak demand, so heavy users can hit slowdowns they didn't budget for.
At $20/month, Private Chat sits above consumer assistants but well below what a compliant self-hosted enclave stack costs to build and maintain. The usage-based Private Inference API competes with ordinary per-token endpoints while adding verifiable isolation at no separate platform fee, and Containers' $20/month plus usage undercuts most managed confidential-computing offerings. Enterprises needing dedicated GPU capacity move to custom pricing.
In short
Tinfoil — Tinfoil runs private AI inference inside hardware secure enclaves so you can cryptographically attest which code and model handled your. Best for Developers shipping AI features that need verifiable, API-level privacy rather than a data-processing promise, Enterprises in defense, legal, and regulated sectors blocked from mainstream providers, Researchers running gray-box interpretability evals on large open model weights. Free to start; paid plans from $20/mo.
What's new in Tinfoil
Checked 6 days agoAcross the latest 2 updates: 1 feature update and 1 news mention.
Safety Without Compromising on Privacy
Tinfoil details its safeguard approach for Tinfoil Chat: pre-hosting model evaluations plus safeguard models running inside secure enclaves.
Architecting Secure Prompt Caching
Tinfoil implemented prompt caching for its Inference API without sacrificing privacy, using client-side cache secrets.
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.
Average across the 5 sources that answered — each source counts once, not each post.
- +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: October 2026
How we score →Key Features
- AI inference inside hardware secure enclaves (TEEs)
- Hardware attestation verified client-side before data is sent
- Open-source attestation SDK for independent verification
- Browser-native verification built with Sigstore and TUF
- Private Chat on web and iOS at $20/month
- End-to-end encrypted chat backups and multi-device sync
- Private web search that does not expose queries
- Speech to text and document upload in Private Chat
- Multi-modal model access in Private Chat
- OpenAI-compatible Private Inference API with usage-based pricing
- Prompt caching using client-side cache secrets (July 2026)
- Safeguard models running inside secure enclaves (September 2026)
- Pre-hosting model evaluations for safety
- Run any Docker image in a secure enclave with Tinfoil Containers
- Multi-GPU enclave execution on NVIDIA Blackwell
About Tinfoil
Tinfoil is a security research lab selling an AI cloud where privacy claims are checkable rather than contractual. Every workload runs inside a hardware secure enclave, and clients verify an attestation before data is sent, so Tinfoil itself cannot see user data. The catalog is split three ways: Private Chat ($20/month) with projects, private web search, speech to text, document upload, multi-modal models, and encrypted sync across browser and iOS; the Private Inference API, an OpenAI-compatible, open-source, usage-based endpoint with per-model token pricing; and Tinfoil Containers, which run any Docker image in an enclave at $20/month plus hourly CPU, memory, and GPU billing. Prompt caching on the API was built with client-side cache secrets (July 2026), a deliberate design so cached prompt material never lands in a form Tinfoil can read. Safeguards follow the same rule: pre-hosting model evaluations plus safeguard models that run inside enclaves (September 2026). Attestation tooling is open source, browser verification is built on Sigstore and TUF, and private observability lets teams confirm what actually executed. Customers skew technical. Maple ships private consumer AI on Tinfoil's confidential GPU inference, Screenpipe serves defense and regulated buyers who cannot touch OpenAI or Anthropic, and Cybera and Syncopate Lab use it for infrastructure and legal work where intellectual property is the blocker. Tinfoil is SOC 2 compliant, runs on Ubuntu and NVIDIA Blackwell multi-GPU enclaves, and collaborates with Red Hat on open confidential AI infrastructure. The positioning is narrow on purpose. Against general-purpose providers you pay more per token for proof rather than a promise; against running local hardware you keep cloud-scale models without owning GPUs. If your data is regulated or your weights are valuable, the enclave overhead is a line item, not a dealbreaker.
Behind the Verdict
Most vendors answer a privacy question with a policy page. Tinfoil answers it with a cryptographic attestation you verify client-side before a token leaves your machine. That distinction is the whole reason to pay the premium, and it holds up across all three products. Pick Private Chat if you want the privacy of a local model with cloud-grade open models behind it. Projects, web search, document upload, speech to text, and sync across browser and iOS are all covered by the $20/month flat fee, and chat billing is per-hour token allowances rather than per-token meter anxiety. Pick the Inference API if you are wiring a product. OpenAI-compatible, open-source, pay-as-you-go, with rate tiers that rise automatically as lifetime paid usage crosses thresholds. The prompt caching work from July 2026 is the interesting part: cache secrets live client-side, so the speedup does not cost you the privacy guarantee that made you choose Tinfoil. Pick Containers if you have a Docker image and a reason to hide it. You pay $20/month plus hourly CPU, memory, and GPU time, with GPUs requiring a monthly commitment and no short on-demand intervals. Persistent volumes bill separately in GB-hours and keep charging after cancellation until you delete them. Watch that one. In practice, the friction is real. Attestation and enclave verification assume an engineer on your side. The enclave overhead on production workloads sits under 10%, which is fine for most inference and noticeable for tight latency budgets. And spending limits on the API are soft: in-flight requests finish and bill, so bound your concurrency if you need a hard ceiling. Where it bites: if you want a free general assistant, the paid tiers here are a privacy tax you do not need to pay. If you are shopping purely on dollars
Researching Tinfoil? Get your full AI stack in 60 seconds.
Free, no signup — tell us your goal and get tools matched to your budget & existing stack.
Real-world workflow fit
Concrete scenarios for the personas Tinfoil actually fits — and what changes day-one when you adopt it.
A healthcare-adjacent product team points its existing OpenAI SDK client at Tinfoil's OpenAI-compatible Private Inference API and verifies the enclave build with the open-source attestation SDK before sending any patient data.
Outcome: Customer data is processed inside a hardware secure enclave with cryptographic proof of which code and model ran, so the compliance review has evidence rather than a vendor statement.
An auditor packages its evaluation harness as a Docker image, deploys it to Tinfoil Containers, and runs gray-box interpretability evals against a 744B-parameter model supplied inside the enclave.
Outcome: Both the auditor and the model owner get cryptographic evidence of exactly what executed, and the weights never leave the enclave.
A consultant uses Private Chat in the browser and on iOS for document upload, speech-to-text notes, and private web search, with encrypted sync keeping the same threads on both devices.
Outcome: Day-to-day AI assistance without exposing queries, uploads, or chat history to a provider that can read them.
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 2026-10-17
Limitations
- Chat is a flat $20/month, while API access is pay-as-you-go with per-model input/output token pricing and Containers are billed per hour for CPU, memory, and GPUs, with GPUs requiring a monthly commitment.
- API rate limits vary by model and usage tier, measured in requests per minute and where applicable tokens per minute, and are shared across all keys in an account or organization; Chat has separate hourly input and output token allowances that reset each clock hour.
- Spending limits and per-key caps are soft, since requests are admitted based on already-recorded usage and only produce a usage record once the response completes.
- Tinfoil does not offer shorter on-demand intervals for Containers, and persistent volumes are billed separately on provisioned GB-hours.
as of 2026-10-02
Verification history
We have re-verified Tinfoil 7 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
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
Showing the 6 most recent of 7 verification passes.
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.
Private Chat
$20/mo
Ideal for
Privacy-conscious professionals, researchers, and small teams who want a daily AI assistant without a compliance project.
What this tier adds
Adds up to 20M input / 1M output tokens per hour, access to projects, web search, speech to text, document upload, multi-modal AI, and sync across web and iOS for $20/month.
Private Inference API
Usage-based
Ideal for
Developers wiring AI into an existing product who need an OpenAI-compatible endpoint with verifiable isolation.
What this tier adds
Usage-based rather than a flat fee; adds open-source, OpenAI-compatible inference in confidential enclaves plus prompt caching with client-side cache secrets.
Tinfoil Containers
$20/mo + usage
Ideal for
Teams deploying Dockerized AI backends, training pipelines, or proprietary models that cannot leave trusted hardware.
What this tier adds
Adds the ability to run any Docker image in a secure enclave, with multi-GPU support for large models, for $20/month plus usage.
Enterprise
Custom
Ideal for
Organizations with specific GPU requirements, procurement terms, or dedicated-capacity needs.
What this tier adds
Custom pricing and terms plus the ability to request GPU access for specific workloads.
Where the pricing makes sense
The company stage and team size where Tinfoil's pricing actually pencils out — and where peers do it cheaper.
At $20/month, Private Chat sits above consumer assistants but well below what a compliant self-hosted enclave stack costs to build and maintain. The usage-based Private Inference API competes with ordinary per-token endpoints while adding verifiable isolation at no separate platform fee, and Containers' $20/month plus usage undercuts most managed confidential-computing offerings. Enterprises needing dedicated GPU capacity move to custom pricing.
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 a developer already holding an API key, the Private Inference API is a drop-in swap in an existing OpenAI SDK client and can be running in minutes. Tinfoil Containers takes longer — one team reported moving off Azure confidential containers to a working Tinfoil deployment in under 20 minutes using the attestation SDK and debug mode. Private Chat requires no setup beyond signing up and logging
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 OpenAI-compatible APIs: point your existing SDK client at Tinfoil's OpenAI-compatible endpoint and verify attestation before cutover.
- →From Azure confidential containers (ACI): move the same Docker image to Tinfoil Containers to skip TLS certificate binding, hardware measurement, and reproducible image digest work.
- →From self-hosted local AI: keep your models open-source and custom while gaining cloud scalability and multi-GPU enclave execution.
- →From a closed-source AI provider: replace vendor assurances with browser-native attestation verification built on Sigstore and TUF.
- ↗To a general-purpose API provider: swap the base URL back in your OpenAI-compatible client, accepting loss of enclave attestation and provable zero retention.
- ↗To self-hosted local AI: run your own weights on your own hardware, trading cloud scalability and multi-GPU enclaves for full local control.
- ↗To another confidential-computing platform: repackage the same Docker image, though you will need to rebuild attestation verification against that platform's tooling.
Integrations
Resources & Guides
Tutorials & Learning
YouTube returned 6 videos for “Tinfoil”, and we withheld 6: 6 could not be judged, because “Tinfoil” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about Tinfoil.
Official links
Tools that pair well with Tinfoil
Common stack mates teams adopt alongside Tinfoil, with the specific reason each pairing earns its keep.
Omnifact
Omnifact is a GDPR-compliant enterprise AI platform with a Privacy Filter™ that masks sensitive data before prompts reach external LLMs.
Blackbox AI
Blackbox AI encrypted inference: route 300+ models through one endpoint with end-to-end encryption and zero data retention.
Push Security
Push Security is browser security for the AI era — it stops AiTM phishing, ClickFix attacks, session hijacking and shadow AI inside the
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 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.
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.
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
Omnifact
Omnifact is a GDPR-compliant enterprise AI platform with a Privacy Filter™ that masks sensitive data before prompts reach external LLMs.
Blackbox AI
Blackbox AI encrypted inference: route 300+ models through one endpoint with end-to-end encryption and zero data retention.
Push Security
Push Security is browser security for the AI era — it stops AiTM phishing, ClickFix attacks, session hijacking and shadow AI inside the
Frequently Asked Questions
Used Tinfoil? Help shape our editorial sentiment research.