Compute together while private details stay apart

MPC lets parties run a shared computation while sensitive user context stays out of one central place

Write the computation. Run it over shares. Open the result your product needs

Compute together while private details stay apart

MPC lets parties run a shared computation while sensitive user context stays out of one central place

Write the computation. Run it over shares. Open the result your product needs

What MPC makes possible

Imagine three hospitals with patient context that could help. Sharing records creates risk. Keeping everything separate slows the work.

Share data: Privacy violations, regulatory issues
Keep data separate: Limited insights, slower progress

Pool records: privacy and compliance risk. Keep everything separate: limited insight and slower progress

With MPC, they compute the approved result together while patient details stay apart.

How it works for builders

MPC works by splitting sensitive data into "shares" - meaningless pieces that only reveal information when combined.

Original secret: 1000
Split into shares:
- Party A gets: 847392847 (random)
- Party B gets: 392847364 (random)
- Party C gets: 847392949 (random)

Individually: Shares reveal nothing
Combined: 847392847 + 392847364 + 847392949 = 1000

MPC works by splitting sensitive values into shares: meaningless pieces that only reveal information when combined. Original value: 1000. Split into shares: Party A gets 847392847, Party B gets 392847364, Party C gets -1240230211. Only together do they reconstruct 1000.

User

Developer

MPC parties

MPC parties

MPC parties

MPC parties

04

Open the allowed result

03

Run the program over shares

05

Receive the result locally

01

Create shares locally

02

Send shares

Choosing the right privacy tool

Choosing the right privacy tool

Use MPC when:

You need teams or systems to compute together without pooling sensitive user context.

Use ZK when:

You need to prove something happened without exposing the details.

Use FHE when:

You need to run computations while private details stay protected.

Use TEE when:

You need hardware-level isolation for processing sensitive code and user context.

Combine them for even more power

MPC

+

ZK

Prove your computation was correct without revealing private details.

MPC

+

FHE

Process sensitive user context across multiple services while keeping it encrypted.

MPC

+

TEE

Speed up secure multi-party computation using trusted hardware.

© 2025 Stoffel Labs Inc. All rights reserved.

© 2025 Stoffel Labs Inc. All rights reserved.

© 2025 Stoffel Labs Inc. All rights reserved.