Mem0 provides a memory layer focused on user personalization.
| Feature | Rice | Mem0 |
|---|---|---|
| Memory Model | Four-component (Working, Episodic, Procedural, Semantic) | User/session scoped facts |
| Learning | Explicit trace commits (Input, Action, Outcome, Reasoning) | Implicit extraction from chat logs via LLM |
| Execution | Integrated procedural memory | External only |
Rice provides distinct memory systems for different purposes: Working (attention), Episodic (traces), Procedural (skills), and Semantic (facts). Mem0 focuses on user facts stored in vector/graph stores.
Rice uses explicit trace commits where agents record Input, Action, Outcome, and Reasoning. Mem0 automatically extracts facts from chat logs using an LLM pipeline.
Rice includes integrated Procedural Memory for running compiled skills. Mem0 is strictly a storage/retrieval layer with no execution capabilities.
Rice is built for agentic systems that need to learn behaviors (how to solve problems). Mem0 excels at user personalization (remembering preferences and facts).