Memory model comparison

Compare memory models first, then evaluate representative tools inside each model. This keeps the focus on guarantees and failure modes rather than brand checklists.

Platform memory

Claude, ChatGPT, Gemini, Copilot. These are the built-in memory features offered directly by model providers. They manage memory behind the scenes, typically as convenience layers tied to a specific product. Platform memory is the easiest to adopt but the hardest to audit, version, or port between providers.

Retrieval memory

Mem0, Zep, LangChain Memory. These systems reconstruct context at query time by embedding past interactions and retrieving the most similar results. They excel at surfacing relevant context but introduce non-determinism: the same question asked twice may surface different facts depending on index state and re-ranking.

File-based memory

Markdown files, JSON stores, CRDT docs. File-based approaches store memory as plain artifacts on disk or in collaborative documents. They are simple and human-readable, but lack schema enforcement, conflict detection, and audit trails unless those are layered on manually.

Deterministic memory

Neotoma. Deterministic memory systems guarantee that the same observations always produce the same entity state. Every fact traces to provenance, every state transition is versioned, and the full history is replayable. Neotoma is the reference implementation of this model, providing the deterministic state evolution, versioned history, and auditable change log guarantees that production agents require.