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Private AI Increase privacy, reduce cost

Privacy by math. Not by promise.

  • Your data, fully privateEncoded on your device. No provider can read it.
  • All types of modelsText, code, vision and reasoning, all private.
  • VerifiableGuarantees you can check, not trust.
Request early information See how it works

You, encrypted in random patterns.

Everyone else, patterns.

Even a state-level actor cannot decode your data.

Illustration: a sphere of thousands of encrypted points with orbiting satellite bands. Twelve random points glow warm, as you, then hand over to a completely new random twelve, again and again, so no single point can be followed.

01The problem

Every prompt you send is an open book.

Open to the AI service provider, the router in between and the LLM cloud provider that runs the model.

  • AI service provider reads it
  • Router sees it
  • LLM cloud provider runs it in plain text

Most AI companies have shown clear signs of training on confidential user data.

What a provider can read, it can keep.

Illustration: your message, “Should I get this checked out?”, glows in plain, readable text, labelled as readable by the AI service provider, the router and the LLM cloud provider.

02How it works

Encoded before it leaves.
Computed unseen.

  1. Encoded on your device

    Your data is encoded client-side, before it goes anywhere.

  2. MPC controls the GPU kernel

    A multi-party computation system drives every call to the GPU kernel.

  3. Computed in a secured area

    The model runs on your encoded data in a secured area of the GPU.

  4. Unreadable to the cloud

    Normally every kernel call is decoded and run in plain text at the cloud provider. With IPRC, it cannot access your inputs or train on them, even if it wanted to.

  5. Same servers, standard GPUs

    No special hardware. It runs on the same servers as standard GPUs.

Illustration: your message becomes an unreadable block of encoded data on your device. A ring labelled MPC drives the calls into a GPU, where the work happens inside a highlighted secured area. Side by side, a standard cloud GPU shows your words in plain text, while the IPRC GPU shows only encoded data. Finally, a standard server with eight ordinary GPUs.

03The future

The more of us who buy privacy, the more everyone has to offer privacy by default.

  1. A premium
  2. A choice
  3. The default

The future depends on it.

And at scale, private AI costs less for everyone.

Illustration: a wide horizon of scattered, dim points. As more people choose privacy, more points light up and settle into one bright, orderly lattice: privacy as the default.

04Trust & security

Verifiable by design.

Privacy by math, not by promise. You don’t have to take our word for it.

  • Encrypted in use

    Not only in transit or at rest. Your data stays encoded while the model computes on it.

  • No single point of trust

    Multi-party computation controls the GPU kernel. Not even the cloud provider sees your inputs.

  • Nothing readable to keep

    No plain text at the provider: nothing to log, leak, sell or train on.

  • Math, not policy

    Every guarantee rests on cryptography you can check, not on a policy you have to trust.

05Request early information

Make privacy the default.

Tell us what you would run privately.

Request early information

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