Sigveil Match
Current prototypeCompare audience overlap across organizations using blinded identifiers and privacy-adjusted aggregate reports.
Private collaboration / Sigveil Match
Understand the audience you share with a partner. Process matching identifiers in your browser and receive an aggregate overlap estimate with privacy controls.
See how a real match worksInside the working app
A campus partnership, using synthetic records.
Actual app screens. Actual matching code.
Name the partnership, choose a privacy setting and copy the invite for your partner.
Each organization selects its own file. The browser normalizes and blinds the matching identifiers.
Both sides apply their session key to the other side's tokens. Matching records produce matching double-blinded tokens.
The coordinator checks group sizes and privacy budget, adds statistical noise, then returns an overlap estimate.

The captured run returned an estimate of 83 (41.5%) after statistical noise, with 1.50 privacy budget remaining. This is demo data, not a customer result.
Try the matching engine
Two synthetic lists. Two fresh session keys. The same browser worker used in the workspace.
student0@school.edu
student1@school.edu
+ 198 sample identifiersstudent0@school.edu
external0@fintech.io
+ 198 sample identifiersNo account or file needed. Both parties run locally for this example; real partners use separate browsers.
Ready when you are. This is a real computation, not an animation.
This local example shows the synthetic intersection before privacy noise. The workspace applies group-size and privacy-budget controls before releasing its aggregate estimate.
The product today, and where it is going.
Compare audience overlap across organizations using blinded identifiers and privacy-adjusted aggregate reports.
Evaluate behavioral evidence of human participation and validate signed attestations before records enter a match. This layer is not implemented yet.
Sigveil Match / Workspace
Create a match room and invite a partner to explore your shared audience.
Name the partnership and create a room for both organizations.
Lower epsilon adds more noise. Each report uses part of the shared privacy budget.
Open a room to prepare local records, invite a partner or view the result.
| Partnership | Partner | Status | Estimate | Action |
|---|
Counts and percentages include statistical noise. They describe audience overlap, not causal conversion lift or newly acquired customers. Org A is the organization that created this room. Account information, room metadata, audit logs and privacy budgets are retained.