Enables agents to audit and repair their long-term memory in Sibyl Memory, detecting contradictions, duplicates, and stale facts, and fixing them with a permanent audit trail.
Provides agents with durable, provenance-aware memory through tools for remembering, recalling, answering, and maintaining information, while structurally resisting injection and confabulation.
Provides persistent long-term memory, knowledge base, and audit trail for AI agents, with intelligent recall, salience tracking, and CJK-aware context management.
Enables AI agents to maintain a local, event-sourced long-term memory with semantic retrieval, decision confidence checks, and proactive recalls, ensuring data never leaves the machine.
Local-first, auditable memory for Codex, Claude Code, and MCP clients. It stores scoped user/project memory in SQLite or Postgres, serves read-only recall and inspection tools by default, and supports opt-in governed writeback with review and forget controls.
Audit-grade memory backbone for agent teams. Bi-temporal facts (event time + transaction time, with recall(as_of=...) replay), 6-step deterministic retrieval (no LLM in the critical path), conversation ingest with speaker-locked dual-pass extraction, per-tenant Postgres row-level security, and Ed25519-signed provenance. Postgres + pgvector + Neo4j defaults.