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SOLUTIONS

Ship apps without creeping on your users. Never see their data again

Stoffel lets you build privacy-first apps. Focus on growing your product, not handling toxic user data.

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Bash

# Initialize a new project from a template

$ stoffel init my-mpc-app --template rust

# Compile StoffelLang to optimized VM bytecode

$ stoffel compile src/main.stfl --binary -O3

# Run a local simulation with 5 parties

$ stoffel dev --parties 5

# Output:

# [✓] Protocol: HoneyBadger MPC Initialized

# [✓] Logic Verified: No single-point-of-failure

# [!] Privacy Guaranteed: Raw data remains local

# Initialize a new project from a template

$ stoffel init my-mpc-app --template rust

# Compile StoffelLang to optimized VM bytecode

$ stoffel compile src/main.stfl --binary -O3

# Run a local simulation with 5 parties

$ stoffel dev --parties 5

# Output:

# [✓] Protocol: HoneyBadger MPC Initialized

# [✓] Logic Verified: No single-point-of-failure

# [!] Privacy Guaranteed: Raw data remains local

Don’t let privacy fears hold your apps’s growth hostage

Status Quo Privacy is killing your velocity. Stoffel separates your logic from raw toxic data

Status Quo

1

At Rest: Encrypt data on the user’s device

2

In Transit: Encrypt it while it moves to your server.

3

Decrypt it to process logic in memory
(Your app just touched toxic data)

4

Your app is a breach magnet.

Stoffel Quo

1

At Rest: Encrypt data on the user’s device

2

In Transit: Encrypt it while it moves to your server.

3

Keep it encrypted while computing.
(Your logic runs on blind inputs)

4

Zero toxic data exposure.

Just build apps. Skip the toxic data

Your users don't want another privacy policy. They want mathematical guarantees their data can't leak.

Get Started Now

Inside the burrow

How the Stoffel Stack protects your data from the inside out.

// Paste a code snippet
import { motion } from "framer-motion";

function Component() {
    return (
        <motion.div
            transition={{ ease: "linear" }}
            animate={{ rotate: 360, scale: 2 }}
        />
    );
}

Define the Logic

Define allowed outputs using Stoffel-Lang (match scores, aggregations, eligibility signals)

// Paste a code snippet
import { motion } from "framer-motion";

function Component() {
    return (
        <motion.div
            transition={{ ease: "linear" }}
            animate={{ rotate: 360, scale: 2 }}
        />
    );
}

Define the Logic

Define allowed outputs using Stoffel-Lang (match scores, aggregations, eligibility signals)

// Paste a code snippet
import { motion } from "framer-motion";

function Component() {
    return (
        <motion.div
            transition={{ ease: "linear" }}
            animate={{ rotate: 360, scale: 2 }}
        />
    );
}

Define the Logic

Define allowed outputs using Stoffel-Lang (match scores, aggregations, eligibility signals)

Constrain at the Source

Constrain at the source so raw data never touches the wire unencrypted

Constrain at the Source

Constrain at the source so raw data never touches the wire unencrypted

Constrain at the Source

Constrain at the source so raw data never touches the wire unencrypted

Compute the Result

StoffelVM runs on encrypted inputs. Nobody sees the raw data. Not you. Not us.

Compute the Result

StoffelVM runs on encrypted inputs. Nobody sees the raw data. Not you. Not us.

Compute the Result

StoffelVM runs on encrypted inputs. Nobody sees the raw data. Not you. Not us.

Verifiable Privacy

Cryptographic proof through your architecture. Not promises in a privacy policy nobody reads.

Verifiable Privacy

Cryptographic proof through your architecture. Not promises in a privacy policy nobody reads.

Verifiable Privacy

Cryptographic proof through your architecture. Not promises in a privacy policy nobody reads.

Toxic Data Kills Products

You are one breach away from losing your users. Stop trading privacy for speed.

What happens when you get breached?

If you're breached tomorrow...

Traditional Architecture

With Stoffel

What leaks

Your user's safety

Gibberish

The fallout

Total Exodus

Zero. No raw data existed

Your legal exposure

"We promised to protect it and failed"

"The system couldn't expose it"

What you lose

Your users

Nothing

Features you didn't think could be private

Complex Features that run entirely on encrypted data

AI/ML

Federated learning aggregation

Train better models without centralizing sensitive data. Compute global weight updates while raw gradients stay distributed.

Learn more

Key Management

Distributed Key Generation

Generate private keys across your company, or partners without a single point of failure.
No liability bomb ticking in your S3 bucket.

Learn more

Build with Stoffel today

Self-host the entire stack and dompute on sensitive data without storing it, sharing it, or trusting anyone to see it.

Application SDKs

Integrate answers-only computation directly into your backend or data science workflows. You send code and encrypted inputs—not raw user data—and receive only the allowed result.

git clone https://github.com/StoffelLabs/Stoffel

Copied

PYTHON

RUST

SOLIDITY

Stoffel-Lang

Write privacy-preserving logic that explicitly defines what outputs are allowed. Stoffel-Lang makes data leakage a compile-time error—not a policy decision.

git clone https://github.com/Stoffel-Labs/Stoffel-Lang

Copied

GitHub: Stoffel-Lang

GitHub: mpc-protocols

Technical Docs

Secure Runtime & Networking

Under the hood, Stoffel runs on a high-performance MPC virtual machine with encrypted, decentralized networking. No party—including you—can access raw inputs.

git clone https://github.com/Stoffel-Labs/StoffelVM

Copied

GitHub: StoffelVM

GitHub: stoffel-networking

Build with Stoffel today

Self-host the entire stack and dompute on sensitive data without storing it, sharing it, or trusting anyone to see it.

Application SDKs

Integrate answers-only computation directly into your backend or data science workflows. You send code and encrypted inputs—not raw user data—and receive only the allowed result.

git clone https://github.com/StoffelLabs/Stoffel

Copied

PYTHON

RUST

SOLIDITY

Stoffel-Lang

Write privacy-preserving logic that explicitly defines what outputs are allowed. Stoffel-Lang makes data leakage a compile-time error—not a policy decision.

git clone https://github.com/Stoffel-Labs/Stoffel-Lang

Copied

GitHub: Stoffel-Lang

GitHub: mpc-protocols

Technical Docs

Secure Runtime & Networking

Under the hood, Stoffel runs on a high-performance MPC virtual machine with encrypted, decentralized networking. No party—including you—can access raw inputs.

git clone https://github.com/Stoffel-Labs/StoffelVM

Copied

GitHub: StoffelVM

GitHub: stoffel-networking

Build with Stoffel today

Self-host the entire stack and dompute on sensitive data without storing it, sharing it, or trusting anyone to see it.

Application SDKs

Integrate answers-only computation directly into your backend or data science workflows. You send code and encrypted inputs—not raw user data—and receive only the allowed result.

git clone https://github.com/StoffelLabs/Stoffel

Copied

PYTHON

RUST

SOLIDITY

Stoffel-Lang

Write privacy-preserving logic that explicitly defines what outputs are allowed. Stoffel-Lang makes data leakage a compile-time error—not a policy decision.

git clone https://github.com/Stoffel-Labs/Stoffel-Lang

Copied

GitHub: Stoffel-Lang

GitHub: mpc-protocols

Technical Docs

Secure Runtime & Networking

Under the hood, Stoffel runs on a high-performance MPC virtual machine with encrypted, decentralized networking. No party—including you—can access raw inputs.

git clone https://github.com/Stoffel-Labs/StoffelVM

Copied

GitHub: StoffelVM

GitHub: stoffel-networking

The Stoffel Stack

Use the full stack or each as you need.

Write code as normal

Mark data as private or public

Stoffel compiler

• Data stays private

• Computation happens

• Results are shared

STOFFEL LANG

Write the computation you want.

Describe analytics, ML steps, matching, or key ops (can be changed for other kinds of algorithms/processes). Mark what can be revealed—we handle the hard parts. Simulate locally and unit test.

Familiar, readable syntax

Secret/public types + explicit reveals

Local simulation and unit tests

Read the Lang guide

STOFFEL VM

Run it reliably. One private result.

SDKs

Drop shared computation into your app.

Write code as normal

Mark data as private or public

Stoffel compiler

• Data stays private

• Computation happens

• Results are shared

STOFFEL LANG

Write the computation you want.

Describe analytics, ML steps, matching, or key ops (can be changed for other kinds of algorithms/processes). Mark what can be revealed—we handle the hard parts. Simulate locally and unit test.

Familiar, readable syntax

Secret/public types + explicit reveals

Local simulation and unit tests

Read the Lang guide

STOFFEL VM

Run it reliably. One private result.

SDKs

Drop shared computation into your app.

FAQ

Have more questions? Contact our team with any questions you may have.

Can't we just anonymize the data?

You already know the answer to this. The moment you join datasets—or someone subpoenas your logs—'anonymized' becomes 're-identifiable.' Anonymization is statistical hope, not cryptographic proof.

Can't we just anonymize the data?

Won't this slow us down?

Compared to what? The three-month security review you're avoiding right now? The slowest part of building privacy-sensitive features is the meetings where you argue about whether you should.

Won't this slow us down?

Compared to what? The three-month security review you're avoiding right now? The slowest part of building privacy-sensitive features is the meetings where you argue about whether you should.

Won't this slow us down?

Compared to what? The three-month security review you're avoiding right now? The slowest part of building privacy-sensitive features is the meetings where you argue about whether you should.

Isn't this massive overkill for our use case?

Depends. Do you prefer 'Yes, but we promise to protect it' or 'No, our architecture makes storing toxic data impossible'?

Isn't this massive overkill for our use case?

Depends. Do you prefer 'Yes, but we promise to protect it' or 'No, our architecture makes storing toxic data impossible'?

Isn't this massive overkill for our use case?

Depends. Do you prefer 'Yes, but we promise to protect it' or 'No, our architecture makes storing toxic data impossible'?

This sounds like research-lab complexity

That's what we thought too. Then we actually tried it. Stoffel is production-ready infrastructure, not an academic prototype. You write logic in a domain-specific language that feels like defining a function signature. The MPC stuff happens under the hood. You ship like a normal developer.

This sounds like research-lab complexity

What's the catch?

Performance overhead for encrypted computation (we're transparent about benchmarks). Learning curve for Stoffel-Lang (not Python, but not assembly either). And you have to actually care about privacy—if you just want legal cover, this isn't it.