Long-term memory for AI agents. Compiles conversations into a structured knowledge base with Claim/Evidence model, source provenance, append-only timeline, and contradiction detection. Multi-path retrieval (Exact + BM25 + Graph + weighted RRF + reranker) — 96.6% R@5 on LongMemEval-S, zero vector dependencies.
A source-grounded memory layer for AI agents that stores, links, and recalls factual memories with confidence levels and citations, enabling honest answers when information is not in the record.
Hermetic memory for AI agents — one Rust binary, one SQLite file, zero network. Recall returns evidence with provenance or abstains: no code path for making things up.
Associative key-graph memory for LLM agents — recall facts by association (recall → read_key → read_memory) instead of vector similarity alone, with persistent cross-session memory and cross-lingual keys.