Basic Memory

Open-source memory for AI agents.

An open-source semantic memory layer for AI agents. Cognee ingests documents, relational data, and system context, then runs an Extract-Cognify-Load pipeline that uses an LLM to build a knowledge graph with embeddings and relationships. Agents query it for durable, cross-session context that captures how concepts connect. Self-host the Python SDK for free, or use the managed cloud tiers.

Memory API that gives any AI agent long-term recall.

Supermemory is a memory and context engine for AI apps. It ingests documents, chat histories, and connector data (Drive, Gmail, Notion), turns them into a searchable store, and serves relevant context back to agents over a single API. It works with any model and ships an MCP server alongside official SDKs.

Long-term memory layer for AI agents. Self-hostable.

Persistent memory store + retrieval pipeline for agent applications. Handles per-user/per-session/per-agent scope cleanly; pairs with OpenAI, Anthropic, and local models.

One API for AI agent memory: ingest, extract, store, retrieve.

A cloud-native platform that gives AI agents semantic memory and operational context through a single API. It ingests documents, audio, video, and web pages, extracts entities and relationships, and handles storage and retrieval so you don't assemble the RAG pipeline yourself. Integrates with frontier models from OpenAI, Anthropic, and Google for extraction.