AI Agent Memory Engine

A local-first persistent memory system for AI agents using SQLite and vector embeddings (MCP/CLI compatible). Solves the problem of stateless AI interactions by enabling agents to remember context across sessions. Target users are AI engineers and builders creating autonomous agents.

The explosion of agentic frameworks—LangChain, CrewAI, AutoGen, and now MCP-compatible tooling—has created a genuine gap: most agents are still stateless by default, and developers are duct-taping memory together themselves. Mem0 is the closest named competitor in the managed memory space, but a local-first, SQLite-backed alternative targets a meaningfully different buyer who won't send context to a third-party API. The $1k–5k/mo band is realistic only as a hosted or licensed product; a pure open-source library with a CLI will attract GitHub stars but struggle to convert to revenue without a clear monetization wedge like a cloud sync tier or team collaboration layer. The biggest risk is commoditization—framework maintainers like LangChain are actively building native memory modules, and if the major agentic platforms ship good-enough built-in persistence, the addressable market shrinks to a niche of developers with specific local or compliance constraints.