Tool Overview:
InfoSum

About InfoSum

InfoSum is a data collaboration platform centered around data clean room technology. The platform enables organizations to connect and analyze datasets without sharing or moving the underlying data. At its core, InfoSum uses a decentralized architecture where data remains within secure environments called 'Bunkers' that are owned and controlled by each organization. This approach addresses growing privacy concerns in data collaboration while allowing companies to derive insights from combined datasets.

What does InfoSum do?

The platform's primary functionality revolves around secure data collaboration through several key technologies. The cornerstone is the Secure Data Clean Room, which processes data locally within each organization's Bunker rather than centralizing it in a shared environment. InfoSum employs differential privacy techniques including redaction thresholds, rounding, and noise injection to protect individual privacy when analyzing data. The platform converts personally identifiable information (PII) into encrypted, non-reversible synthetic IDs that are specific to each collaboration and time period.

InfoSum's Private Path technology enables organizations to send and receive enriched data intelligence without exposing the underlying personal data. Through this system, companies can match and analyze customer data across partners while maintaining strict privacy controls. The platform provides granular permission settings that define what data can be used, for what purpose, at what level of detail, and for how long - down to individual attributes.

What makes InfoSum different?

A key technical differentiator is InfoSum's 'non-movement of data' approach. Rather than copying or transferring data between parties, all processing occurs locally within each organization's secure Bunker. The platform creates mathematical models that abstract the data in ways that prevent enumeration or extraction while enabling analysis across datasets. This architecture eliminates the security risks associated with traditional data lakes or warehouses that centralize sensitive information.

The platform's identity resolution capabilities operate without reliance on a single identity graph or vendor. Organizations can choose from multiple identity partners to resolve customer identities across datasets. When analyzing overlapping customers between partners, InfoSum calculates match rates without exposing the actual matching keys. All results are presented at an aggregate statistical level with privacy-preserving techniques applied to prevent re-identification of individuals.

Use cases and industries

InfoSum serves multiple sectors including retail media, advertising, and financial services. In retail media networks, the platform enables retailers and brands to match customer data for targeted advertising while protecting shopper privacy. Media companies use it to help advertisers measure campaign effectiveness by connecting exposure data to sales outcomes without sharing raw transaction data.

The platform supports various data collaboration scenarios: connecting internal data silos to create unified customer views, enabling second-party data sharing between direct partners, and facilitating multi-party data networks. Common applications include audience planning, campaign measurement, identity resolution, and consumer insights generation. InfoSum provides drag-and-drop tools aimed at business users rather than data scientists, though the underlying privacy architecture maintains strict controls on how data can be accessed and analyzed.