---
schema_version: "newruntime-agent-readable-v0.1"
type: "post"
slug: "cognee-agent-memory-platform"
title: "Cognee Packages Agent Memory as a Self-Hosted Knowledge Graph"
description: "Cognee matters less as another memory SDK and more as an attempt to package persistent agent memory through ingestion, graph/vector search, ontology, and self-hosting."
status: "published"
published_at: "2026-07-21"
topics: ["agent-memory","knowledge-graph","open-source"]
source_urls: ["https://github.com/topoteretes/cognee"]
routes: {"html":"https://newruntime.com/posts/cognee-agent-memory-platform/","markdown":"https://newruntime.com/posts/cognee-agent-memory-platform.md","json":"https://newruntime.com/posts/cognee-agent-memory-platform.json"}
source_format: "markdown"
---

# Cognee Packages Agent Memory as a Self-Hosted Knowledge Graph

Cognee is an open-source AI memory platform for agents. The important signal is not just the repository, but the packaging of memory as infrastructure: ingestion, knowledge graph, vector search, ontology, integrations, and self-hosted deployment.

Agent memory is becoming a separate market because ordinary RAG does not answer the harder questions: what should an agent remember between tasks, who verified it, what is stale, and which context can safely enter the next run.

## Why it is worth tracking

Agent memory requires:

- provenance;
- schemas for facts;
- deduplication;
- long-term storage;
- a forgetting policy;
- links between episodic traces and reusable knowledge.

## New Runtime Read

Agent memory is not "put everything in a vector database". It is operational memory: what was done, what was proven, what can be reused, and which records must not enter the next context without review.