Modern AI agents need persistent, searchable memory to maintain context across conversations and tasks. Inspired by OpenClaw's memory architecture, sqlite-memory implements what we believe will become the de facto standard for AI agent memory systems: markdown files as the source of truth.
In this paradigm:
* Markdown files serve as human-readable, version-controllable knowledge bases
* Embeddings enable semantic understanding and retrieval
* Hybrid search combines the precision of full-text search with the intelligence of vector similarity
sqlite-memory bridges these concepts, allowing any SQLite-powered application to ingest, store, and semantically search over knowledge bases.
Modern AI agents need persistent, searchable memory to maintain context across conversations and tasks. Inspired by OpenClaw's memory architecture, sqlite-memory implements what we believe will become the de facto standard for AI agent memory systems: markdown files as the source of truth.
In this paradigm:
* Markdown files serve as human-readable, version-controllable knowledge bases
* Embeddings enable semantic understanding and retrieval
* Hybrid search combines the precision of full-text search with the intelligence of vector similarity
sqlite-memory bridges these concepts, allowing any SQLite-powered application to ingest, store, and semantically search over knowledge bases.