Product 03 · The data clean room · Early access
Two companies. One answer.
Zero records exchanged.
Share Without Sharing is a neutral data clean room built on private set intersection and federated analysis. Two organizations bring encrypted data; the room computes the answer — overlap counts, match rates, aggregate measurements — and that answer is the only thing either side ever sees. Not a data-sharing agreement with extra steps: an environment where sharing is architecturally impossible.
The problem
The most valuable questions
sit between two companies.
Which of our fraud cases has the other bank seen? How many of our customers did that campaign actually reach? Every one of these questions dies today in the same place: legal, correctly, refusing to email a customer list.
Mule networks exploit the walls
Fraud rings rotate across banks and remittance corridors precisely because institutions can't compare notes without breaking the law.
Campaigns can't be verified
Advertiser and publisher each hold half the truth. Reconciling exposure to outcome usually means one side surrendering its data to the other.
M&A diligence goes blind
"How much do our customer bases overlap?" is a nine-figure question routinely answered by guesswork, because answering it properly would leak the asset itself.
How it works
Private set intersection,
operated by a neutral party.
Each side keeps its data
Records are hashed and encrypted on each organization's own infrastructure before anything is submitted. Raw lists never travel.
The room computes blind
Private set intersection finds matches without decrypting either input. Clean Lava operates the room and can't see the records either.
Only aggregates leave
Overlap counts, match rates, and measurements — with differential-privacy noise — are released to both parties. Individual matches are never revealed.
Guarantees
You get the answer.
Never the records.
- No raw exchange, by construction. The protocol computes on encrypted inputs; there is no step at which either party could see the other's list.
- Neutral operator, blind operator. Clean Lava runs the room but holds no decryption capability over either input.
- Aggregate-only outputs. Minimum cohort sizes and differential-privacy noise make individual re-identification from results statistically implausible.
- A lawful basis your counsel can sign. Designed against NDPA 2023 and GDPR data-minimization requirements — the point is that legal can finally say yes.
Early access
Have a question stuck between two companies?
Fraud-list overlap pilots between two institutions are where we're starting. Bring your counterpart; we'll bring the room.