Why I Developed Local-First Agent Memory
LoreConvo introduces a local-first memory layer using SQLite and FTS5, offering an alternative to traditional vector embedding methods.
AI agents typically rely on vector embeddings for memory management, which can introduce hidden costs like network latency and dependency on external models. In developing LoreConvo, I aimed to demonstrate that a well-optimized full-text search engine could provide efficient recall without these drawbacks. By utilizing SQLite and FTS5, I created a local-first memory layer that operates offline and allows users to maintain control over their data.