Sigveil Shared insights.
Private data.
PRIVATE MEASUREMENT
Working prototype

Private collaboration / Sigveil Match

Find common ground.
Keep your records private.

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 works
01
Your matching records stay local Identifiers are normalized and blinded in your browser before token exchange.
02
Shared answers, with privacy controls Minimum group sizes, statistical noise and a query budget constrain reporting.
03
A report you can understand See estimated overlap and the remaining privacy budget in one place.
Your records → blinded tokens → Shared insight ← blinded tokens ← Partner records
01 / Your workspace

Make room for a better partnership.

Create a workspace, invite your partner and prepare your first private match.

Account details are stored for sign-in. The local-processing promise applies to matching identifiers, not your account information.

Inside the working app

Two lists. One shared answer.

A campus partnership, using synthetic records.
Actual app screens. Actual matching code.

  1. 01

    Create a match room

    Name the partnership, choose a privacy setting and copy the invite for your partner.

  2. 02

    Prepare each list locally

    Each organization selects its own file. The browser normalizes and blinds the matching identifiers.

  3. 03

    Exchange blinded tokens

    Both sides apply their session key to the other side's tokens. Matching records produce matching double-blinded tokens.

  4. 04

    Read the aggregate report

    The coordinator checks group sizes and privacy budget, adds statistical noise, then returns an overlap estimate.

Captured from Sigveil Match
Actual Sigveil workspace showing a completed campus partnership match with synthetic records.
A real workspace after the sample match: 200 records per organization, with 80 deliberately shared identifiers.

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

Run it. Watch the tokens change.

Two synthetic lists. Two fresh session keys. The same browser worker used in the workspace.

School / 200 recordsstudent0@school.edu
student1@school.edu
+ 198 sample identifiers
Partner / 200 recordsstudent0@school.edu
external0@fintech.io
+ 198 sample identifiers

No account or file needed. Both parties run locally for this example; real partners use separate browsers.

  1. 01 / Prepare the sample lists
  2. 02 / Blind each list locally
  3. 03 / Apply the other session key
  4. 04 / Compare the token sets

Ready when you are. This is a real computation, not an animation.

One platform. Two complementary layers.

The product today, and where it is going.

Sigveil Match

Current prototype

Compare audience overlap across organizations using blinded identifiers and privacy-adjusted aggregate reports.

Sigveil Verify

Planned

Evaluate behavioral evidence of human participation and validate signed attestations before records enter a match. This layer is not implemented yet.