RyuMem – Persistent memory layer for agentic workflows and LLMs

Summary: RyuMem provides a deterministic, queryable memory layer that stores and reasons over long-term context, capturing state, decisions, and relationships for AI agents. It enables agents to maintain a system of record beyond simple retrieval of embeddings, improving continuity in complex workflows.

What it does

RyuMem stores and recalls persistent context for agentic systems, allowing reasoning over past states and decisions rather than resetting when context becomes complex.

Who it's for

It is designed for developers and teams building AI agents and LLM applications that require reliable long-term memory management.

Why it matters

It solves the problem of agents losing track of prior states and decisions, enabling consistent reasoning over evolving workflows.