Results for “semantic-memory”

Builds a local RAG memory system that indexes session logs and notes into ChromaDB for semantic recall across agent restarts.

Stores, retrieves, and curates persistent facts in a structured memory map, distinguishing between user facts and reference text.

Persists and recalls agent knowledge across sessions using four approaches: static KB, company wiki, persistent memory, and session brain.

Persists context across sessions by compiling sources into a local SQLite store and markdown tree, then retrieves relevant memory via embedding search.

Organiza y guarda memoria en Engram automáticamente, clasificando cada conocimiento por tipo y área, y consultando el contexto al iniciar sesión.

Structured memory system with domains, decay, and links for AI agents, replacing flat memory files with a weighted, interconnected memory palace.

Builds a personal knowledge base for capturing and retrieving understanding, with structured namespaces for concepts, tools, patterns, and references.

Indexes document metadata in SQLite and manages ephemeral key-value state in Redis for cross-session context.

Guarda y consulta información en Engram automáticamente para mantener contexto entre sesiones, optimizando el uso de tokens y delegando exploración compleja.

Manages a multi-layered knowledge system for ingesting, organizing, syncing, and retrieving knowledge across local files, MCP memory, vector stores, and Git repos.

Routes requests into the correct obsidian-mind mode: install, daily session loop, capture, review, maintenance, multi-agent wiring, or semantic search, using a ready-made Obsidian vault template for persistent agent memory.