Cognee is an open-source AI memory engine that enhances LLM accuracy by creating knowledge graphs from various data sources, enabling more reliable and context-aware AI responses.
https://www.cognee.ai/?ref=aipure
cognee

Product Information

Updated:May 16, 2025

cognee Monthly Traffic Trends

cognee received 11.1k visits last month, demonstrating a Significant Decline of -50.4%. Based on our analysis, this trend aligns with typical market dynamics in the AI tools sector.
View history traffic

What is cognee

Cognee is a Python-based semantic layer designed to improve AI applications and agents by providing them with reliable memory capabilities. It acts as a bridge between raw data and LLMs, offering a sophisticated way to structure, store, and retrieve information. As an open-source tool, it can be deployed on users' own systems, ensuring data control and regulatory compliance. The platform supports multiple data types including unstructured text, media files, PDFs, and tables, making it versatile for various use cases.

Key Features of cognee

Cognee is an open-source AI memory engine that enhances LLM accuracy by creating knowledge graphs from various data sources. It implements scalable, modular ECL (Extract, Cognify, Load) pipelines to process and connect data, resulting in more reliable AI responses with claimed 90% accuracy out of the box. The system supports multiple data types, uses RDF-based ontologies for smart data structuring, and can be deployed on-premises for data security.
Flexible Data Integration: Supports over 28 data sources and multiple types including unstructured text, PDFs, tables, and media files, with customizable storage options for vector and graph databases
Smart Knowledge Mapping: Creates comprehensive knowledge graphs using RDF-based ontologies to establish relationships between data points and enable actual reasoning rather than pattern matching
Scalable Architecture: Handles large volumes of data through distributed systems, scaling from gigabytes to terabytes while maintaining performance
Secure Deployment Options: Offers both cloud and on-premises deployment options, ensuring data security and regulatory compliance

Use Cases of cognee

Customer Service Enhancement: Improves customer support by providing agents with personalized response suggestions based on user history and context, as demonstrated in the Dynamo gaming case study
Content Generation and Analysis: Enables more accurate text generation, content summaries, and translations by providing LLMs with better context and relationships
Code Generation Support: Assists in generating more reliable and context-aware code by maintaining relationships between code components and documentation

Pros

Free and open-source availability
High flexibility with customizable storage options
Strong security through on-premises deployment option
Advanced ontology-based data structuring

Cons

Requires technical expertise to implement and customize
May need significant computational resources for large-scale deployments

How to Use cognee

Install Cognee: Install using pip, poetry or other Python package managers. For basic installation: 'pip install cognee'. For PostgreSQL support: 'poetry add cognee[pg]'
Configure Environment: Set up environment variables or create a .env file for database and LLM provider settings. For PostgreSQL: set cognee.config.db_provider = 'postgres' and configure connection string
Initialize Basic Usage: Import cognee and use async/await patterns since Cognee is asynchronous by design. Basic structure: 'import cognee; import asyncio'
Add Data: Use cognee.add() to input your data. Cognee accepts various data types including text, PDFs, tables, media files, etc.
Generate Knowledge Graph: Call 'await cognee.cognify()' to process the data and create knowledge graph connections
Query the Knowledge Graph: Use 'await cognee.search()' to query your data and get relevant responses
Optional: Configure Custom Storage: Choose and configure your preferred database provider (vector or graph databases) by following the documentation
Optional: Set Up Ontologies: Define data structure using RDF-based ontologies to make data relationships smarter
Deploy: Run everything on your own servers for data security and control. Cognee supports both small and large-scale deployments

cognee FAQs

Cognee is an open source AI memory engine that helps improve AI agent responses by mapping and connecting data points logically. It creates knowledge graphs from various data sources to enable more accurate and reliable AI responses.

Analytics of cognee Website

cognee Traffic & Rankings
11.1K
Monthly Visits
#1520165
Global Rank
-
Category Rank
Traffic Trends: Feb 2025-Apr 2025
cognee User Insights
00:01:11
Avg. Visit Duration
3.15
Pages Per Visit
48.56%
User Bounce Rate
Top Regions of cognee
  1. US: 34.92%

  2. IN: 22.48%

  3. FR: 9.86%

  4. TR: 4.62%

  5. BR: 3.97%

  6. Others: 24.15%

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