Agents accumulate long-term records of user statements and behaviors with no disclosure, consent layer, or mechanism for users to inspect, correct, or delete what is retained. This creates a structural asymmetry where agents hold more complete records of users than users can access themselves. No marketplace or infrastructure layer exists to manage memory provenance, consent grants, or user-side data rights across agent deployments.

Users have zero visibility into what AI agents remember about them and no ability to inspect, revoke, or port that memory — creating a massive trust and compliance gap as persistent-memory agents proliferate.

AI agent developers who need GDPR/CCPA-compliant memory handling, and privacy-conscious professionals who interact with multiple AI agents daily across work and personal contexts.

GDPR/CCPA enforcement is intensifying and agent memory is an unaddressed compliance gap — developers will pay to avoid fines, and enterprises will mandate consent infrastructure before deploying memory-enabled agents at scale.

MVP is a two-sided protocol: (1) a user-facing dashboard showing a unified view of all memories held by connected agents with inspect/correct/delete controls, and (2) a developer SDK (middleware) that intercepts memory-write events, logs provenance, and enforces consent policies — ship SDK-first for LangChain/CrewAI ecosystems.

Adjacent privacy/consent management (OneTrust, etc.) is a $3B+ market; agent-specific memory governance is greenfield with every agent deployment becoming a customer node.