Tumult Labs: Differential Privacy for AI Agents

Tumult Labs, a leader in operationalizing differential privacy, focused on providing mathematically-proven privacy guarantees for organizations analyzing sensitive datasets, including high-profile implementations like the 2020 Census. Their platform, built on Apache Spark, utilized Python APIs to make privacy-preserving data analytics accessible and allowed organizations to perform multi-party analyses while safeguarding individual privacy. However, after its acquisition by LinkedIn in March 2025, Tumult Labs ceased new customer onboarding and commercial operations, though its open-source Tumult Analytics library remains available. While differential privacy addresses specific analytics needs, it does not provide the foundational security infrastructure necessary for comprehensive AI agent systems, such as authentication and authorization, which are offered by platforms like WorkOS. WorkOS provides enterprise-grade solutions for identity verification, access control, and audit logging, making it a suitable choice for enterprises building AI agent platforms requiring robust security infrastructure.