Introduction to Tinfoil

AI is going to permeate every aspect of our lives. If you are a developer, there is a chance that you are using Copilot or Cursor to help you code. If you are a radiologist, you are probably using image recognition pipelines to help you diagnose your patients faster. If you are using a messaging app or any social network, some level of moderation might be happening using large language models. If you are reading this, you might even be building AI-powered software yourself.

The problem with AI-as-a-Service

Unfortunately, all AI-powered applications require significant processing power, too much to run locally on the end-user's device. Instead, they send requests to servers that run the latest — and largest — AI models on specialized hardware. Every piece of software is becoming distributed on third parties servers and services. Because this is the only way to integrate powerful AI models into products, more private data than ever is now being sent to these third-party servers, and users need to trust a long series of parties: the SaaS providers, the company that provides the AI model as-a-service (e.g., OpenAI), and the cloud provider (e.g., Azure). This opens up the door for privacy violations and data breaches: there is no way for the end-user to check these parties are keeping their "pinky promises" to handle user's data properly — by not collecting, training on or selling private data to interested third parties.

For a privacy-minded company with enough resources like Apple, building special infrastructure to prevent themselves from accessing user private data is possible. But for other companies, there are currently no easy solutions to provide customers with satisfactory levels of confidentiality. The best you can do is to blindly trust third-party API providers and convince your own customers to trust you for not mishandling their data. In practice, people and companies are reluctant to use products that use AI-as-a-service. This is expected when companies regularly violate their privacy policies and are constantly vulnerable to data breaches.

Our mission

At Tinfoil, we are building something different: a platform to deploy AI and other SaaS products with strong confidentiality guarantees. The way we see it, AI is becoming an extension of local software that used to have a physical security boundary. With Tinfoil, we are extending these same physical security boundaries to the cloud, thanks to secure hardware enclaves. This makes it possible to run AI-powered applications in the cloud with security guarantees similar to on-prem solutions.

What makes Tinfoil different?

In traditional cloud computing, isolation is one directional and hierarchical. There are no verifiable mechanisms to isolate private user data from software managed by the cloud or the service provider. At Tinfoil, we leverage secure enclaves and confidential computing — a series of hardware mechanisms present in the latest server-grade CPUs and GPUs — to isolate sensitive workloads at the hardware level. Additionally, these security claims can be automatically verified at every connection. This ensures that users' private data is never accessible to any other software running on the same machine or third party, and that trust is replaced with verifiable security. This provides the highest level of security currently available in cloud computing.

The Tinfoil guarantee:

No access to customers' private data. Not for you, not for us, not for the cloud provider, not for third parties. All supported by verifiable security claims users can check for themselves. Everything stays encrypted, and the user's device security boundaries are securely extended to only include the hardware enclave.

Use cases

The Future of AI is Private

As AI continues to transform every industry — from software development to social media — the need for privacy has never been more critical. Join us in building a future where privacy and AI innovation go hand in hand. Contact us to learn more about how Tinfoil can help you deploy AI with confidence.

Further reading

To understand how we've built Tinfoil on top of these mechanisms, you can read our technical overview of Tinfoil enclaves. You can also read how we built trust in our platform by using a combination of open source code, automated builds, transparency logs, and remote attestation.