Data clean rooms & privacy-enhancing tech · InfoSum Ltd.

InfoSum

Decentralized data clean room where partners match and analyze audiences without either side's raw data ever leaving its owner.

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InfoSum's clean room is built on a decentralized model: each participant's data stays in its own environment (InfoSum calls this a 'bunker'), and matching happens by comparing mathematical representations of records rather than moving or pooling raw data between the two sides. Brands, retailers, agencies and media owners use it to find overlap between their respective customer bases and measure campaign performance without either party exposing individual-level records to the other. Its 'Private Path' product extends the same architecture to direct, permissioned collaboration between two specific organizations rather than a shared multi-party environment. It positions itself against centralized clean rooms (where a third party or one partner hosts the combined dataset) as a lower-exposure alternative for identity and measurement use cases in advertising.

At a glance

Vendor InfoSum Ltd.
Pricing model Quote only
Free tier No
Deployment Cloud
Open source No
Best for Advertisers and publishers who want audience matching and measurement without centralizing either party's raw data.

Pricing

Enterprise pricing quoted per engagement; no public price list.

Pricing has not been verified yet — see the vendor's site.

Features

  • Decentralized matching without raw data movement
  • Data Clean Room for multi-party audience overlap and measurement
  • Private Path for direct bilateral collaboration
  • Identity resolution layered on top of the matching engine
  • Cross-cloud connectivity between partners' own environments
  • Audience segmentation and activation without data pooling

Integrations

Profile last reviewed September 21, 2026

Head to head

Alternatives

LiveRamp Clean Room LiveRamp's clean room, built on the acquired Habu technology, for cross-cloud data collaboration tied to LiveRamp's identity graph. Decentriq Confidential-computing clean room that runs analysis inside hardware-encrypted enclaves so no party, including Decentriq, can see the raw data. Optable Identity and clean-room platform for publishers and advertisers to collaborate on audiences without exposing raw data.

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Terms to know

First-party data Data a company collects directly from its own customers and properties, rather than acquiring it from outside sources. Customer segmentation Dividing a customer base into groups that share meaningful traits so each can be targeted or served differently. Data governance The policies, roles and processes that determine how data is defined, owned, accessed and kept compliant. Data clean room A controlled environment where two or more parties analyze combined data together without either side seeing the other's raw records. Identity resolution Matching data from different sources and devices to a single underlying person or household despite no shared identifier.

Related guides

How to choose a data clean room Pick a data clean room by who you need to collaborate with, which cloud you're both on, and how strong a privacy guarantee the use case actually requires.