Mem0, Zep, LangChain, Letta: A Technical Breakdown of AI Memory Architectures

Four prominent AI memory frameworks — Mem0, Zep, LangChain Memory, and Letta — each claim to solve conversational memory but use fundamentally different approaches under the hood. LangChain's memory classes are modular building blocks that give developers full control but require them to handle conflict resolution and storage logic themselves. Mem0 uses a two-stage LLM process to extract facts and reconcile contradictions, automatically updating or deleting stale information rather than accumulating conflicting entries. This conflict-resolution step addresses a core weakness in simpler vector-store approaches, where outdated facts can persist alongside newer ones and skew retrieval results. The choice between these tools depends on use case: LangChain suits developers building custom pipelines, while Mem0 targets multi-session products where user facts evolve over time.