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InfoSum vs LiveRamp Clean Room

InfoSum keeps each partner's data in its own environment and matches on mathematical representations; LiveRamp centers multi-cloud collaboration on RampID.

Side by side

InfoSum LiveRamp Clean Room
Vendor InfoSum Ltd. LiveRamp Holdings, Inc.
Pricing model Quote only Quote only
Free tier No No
Deployment Cloud Cloud
Open source No No
Best for Advertisers and publishers who want audience matching and measurement without centralizing either party's raw data. Brands and publishers running multi-cloud, multi-party data collaboration tied to a shared identity layer.
Pricing

Enterprise pricing quoted per engagement; no public price list.

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

Enterprise pricing quoted per engagement; no public price list found.

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
  • Cross-cloud collaboration (Snowflake, Databricks, BigQuery)
  • Configurable aggregation thresholds on query results
  • Integration with RampID identity resolution
  • Incrementality and overlap analysis templates
  • Query review and governance controls
  • Multi-party (not just two-party) collaboration support

Verdict

Both InfoSum and LiveRamp Clean Room serve the advertising and media use case — audience overlap, campaign measurement — but their underlying architecture differs. InfoSum is built as a decentralized model: each participant's data stays in its own "bunker" permanently, and matching happens by comparing mathematical representations of records rather than moving or pooling raw data anywhere, even inside a shared clean room. LiveRamp's clean room (built on the acquired Habu technology) works across multiple collaborators' cloud data platforms — Snowflake, Databricks, BigQuery — and leans on LiveRamp's own RampID identity graph to match people across datasets that use different identifiers natively.

Choose InfoSum if

  • You want the strongest architectural guarantee that raw data never leaves either party's own environment, even during matching.
  • Your collaboration is primarily bilateral (its "Private Path" product is built for two specific organizations working directly together).
  • You're not already invested in LiveRamp's identity infrastructure and don't need it.

Choose LiveRamp Clean Room if

  • You need multi-cloud, multi-party collaboration — more than two organizations, potentially on different data platforms — not just a bilateral match.
  • You already use, or want to use, LiveRamp's RampID for person-level identity resolution across your partner ecosystem.
  • Configurable aggregation thresholds and query review on top of an established identity graph matter more than a fully decentralized architecture.

What they share

Both are quote-only with no public price list, both are aimed squarely at advertising and media use cases rather than general-purpose data collaboration, and both position themselves as lower-exposure alternatives to a model where one party simply hosts the combined dataset. Neither is a fit for non-advertising use cases (healthcare data collaboration, cross-institution fraud analysis) — for those, a confidential-computing clean room such as Decentriq or a cloud-native option is the more relevant comparison.

Last reviewed September 22, 2026

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