Cross-Session Identity Resolution In Agent Memory

Persistent AI-agent memory depends not only on storing information across sessions but on correctly resolving each session to the right person, since using a device or other shared identifier can cause one user’s preferences or sensitive data to overwrite or appear in another’s context. Mem0 scopes memories through identifiers such as user_id, agent_id, app_id, and run_id, but it does not determine which identifier belongs to the current human; applications must maintain that identity mapping themselves. Effective identity resolution must unify signals belonging to one person, isolate distinct people to prevent privacy leaks, and merge duplicate identity graphs when accounts are later recognized as the same user. The recommended approach combines deterministic signals, such as verified email or authenticated SSO identity, with cautious probabilistic scoring of weaker signals like device and name, using high thresholds for automatic links and a review band for ambiguous matches. Because an incorrect merge can expose confidential information while a missed match mainly causes fragmented personalization, systems should prioritize avoiding collisions, retain provenance for auditable and reversible merges, and keep anonymous-session memory provisional until a reliable identity match is established.

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