airweave open source analysis
Context retrieval for AI agents across apps and databases
Project overview
⭐ 5186 · Python · Last activity on GitHub: 2025-11-16
Why it matters for engineering teams
Airweave addresses the challenge of efficiently retrieving relevant context for AI agents from multiple applications and databases, which is crucial for building intelligent systems that rely on large language models. It is particularly well suited for machine learning and AI engineering teams looking for a production ready solution to integrate context retrieval seamlessly into their workflows. The project is mature enough for production use, with a solid user base and active maintenance, making it reliable for real-world applications. However, it may not be the best choice for teams seeking a lightweight or fully managed service, as it requires self hosting and some setup effort. Additionally, if your use case involves simpler search needs without vector database integration, alternative tools might be more straightforward to implement.
When to use this project
Airweave is a strong choice when your project demands advanced context retrieval combining knowledge graphs, vector databases, and large language models in a self hosted option for AI agents. Teams should consider alternatives if they require minimal configuration or prefer fully managed cloud services without the need for extensive customisation.
Team fit and typical use cases
This open source tool for engineering teams is most beneficial to machine learning engineers and AI specialists who integrate complex search and retrieval capabilities into their products. They typically use Airweave to enhance AI agents with relevant context from diverse data sources, supporting applications such as intelligent assistants, knowledge management systems, and search-driven AI solutions.
Best suited for
Topics and ecosystem
Activity and freshness
Latest commit on GitHub: 2025-11-16. Activity data is based on repeated RepoPi snapshots of the GitHub repository. It gives a quick, factual view of how alive the project is.