Leviathan Brings Ranked Memory To Agents

Leviathan’s strongest idea is not another vector database; it is disciplined retrieval that keeps agent context small, inspectable, and deployable.

• –BM25 ranking and cited result cards make answers easier to audit than raw dumps or opaque semantic retrieval
• –The single static binary and SQLite index reduce operational overhead for local, self-hosted workflows
• –Group filters, date ranges, upserts, deletes, and ambiguity handling fit real support-ticket and operations datasets
• –Optional MCP and agent wrappers make integration practical across coding agents and developer environments
• –Its lexical search will be weaker for synonyms and conceptual matches than embedding-based systems, so hybrid retrieval may still be needed