Cognee vs Sanctum

Cognee turns documents, chats, tickets, and API data into graph memory language model agents can recall across sessions. It builds linked entity graphs from that context so agents stop restarting from scratch each run. You can connect Slack, GitHub, or Linear so coding agents and support bots share one permission-aware company brain.

Plain RAG returns similar text chunks. Cognee pairs vector search with knowledge graphs and auto-generated ontologies, so recall pulls connected entities and cited facts rather than isolated snippets. The SDK centers on four verbs, remember, recall, forget, and improve, and the same surface ships over HTTP and MCP for Claude Code, Codex, and OpenClaw.

Platform teams use it for coding agent memory, GraphRAG pipelines, deal intelligence, and customer-facing agents that need grounded answers. Run it with pip locally, self-host in Docker or on-prem, or move to Cognee Cloud when you want managed scale. The project reports 30.4k GitHub stars and 5M+ SDK runs per month, with production deployments at Bayer and Knowunity.

Introducing Sanctum, your private, local AI Assistant that brings the sophistication of AI directly to your desktop with maximum privacy and convenience. Optimized for MacOS 12+ with support for both Apple Silicon and Intel processors, Sanctum is an innovative tool that enables you to run and interact with feature-rich open-source Large Language Models (LLMs) right on your local machine. Forget the cloud - your data is encrypted, secure, and stays within the confines of your device, providing unrivaled privacy. Whether for personal use, data-sensitive tasks, or development projects, Sanctum takes a privacy-first approach to ensure that your AI interactions remain your own. With an anticipated mobile version and forthcoming updates like additional model support and multi-platform compatibility, Sanctum promises to be at the forefront of accessible and secure AI tools.