What is DeepSearcher used for?

DeepSearcher from Zilliz is an open-source deep research tool that uses LLMs and vector databases like Milvus to reason over private data and write reports. It is a good fit for enterprise knowledge search with LLMs, generating research reports from internal documents and experimenting with agentic RAG.

Is DeepSearcher open source?

Yes. DeepSearcher is open source under the Apache-2.0 licence. Its source code is on GitHub at zilliztech/deep-searcher and is written mainly in Python.

Is DeepSearcher free?

Yes. DeepSearcher is open source, so the software itself is free to use.

Can I self-host DeepSearcher?

Yes. DeepSearcher can be self-hosted on your own server or infrastructure.

What is DeepSearcher an alternative to?

DeepSearcher is an open-source alternative to Reason. Other open-source alternatives to Reason include LMMS and Ardour.

Is DeepSearcher actively maintained?

Yes. The most recent commit to DeepSearcher was on 22 September 2026. The project has 8.3k stars on GitHub.

DeepSearcher: open-source alternative to Reason

About DeepSearcher

This entry covers DeepSearcher, the open-source project from Zilliz, the company behind the Milvus vector database. It is pitched as an alternative to deep research services for reasoning and searching over private data, and it is written in Python.

DeepSearcher pairs large language models, including OpenAI models, Qwen3, DeepSeek, Grok, Claude and Llama, with vector databases such as Milvus and Zilliz Cloud to search, evaluate and reason over your documents and produce an answer or a comprehensive report. Listed features are private data search that can also bring in online content, vector database management with data partitioning, a choice of embedding models, support for multiple LLMs, and a document loader for local files, with web crawling in development.

It installs with pip, using a virtual environment and Python 3.10, or in development mode with uv, and the quick-start demo needs an OpenAI API key in the environment. The project is licensed under Apache-2.0 and suits enterprise knowledge management, question answering and information retrieval experiments.

Key features

Deep research over private data
Milvus and Zilliz Cloud vector storage
Multiple LLM provider support
Choice of embedding models
Local file document loader
Reports generated from retrieved evidence

Good fit for

→Enterprise knowledge search with LLMs
→Generating research reports from internal documents
→Experimenting with agentic RAG

Built with: Python
Tags: deep-research; rag; agentic-rag; llm; vector-database; milvus; python; private-data; zilliz

DeepSearcher: questions and answers

What is DeepSearcher used for?: DeepSearcher from Zilliz is an open-source deep research tool that uses LLMs and vector databases like Milvus to reason over private data and write reports. It is a good fit for enterprise knowledge search with LLMs, generating research reports from internal documents and experimenting with agentic RAG.
Is DeepSearcher open source?: Yes. DeepSearcher is open source under the Apache-2.0 licence. Its source code is on GitHub at zilliztech/deep-searcher and is written mainly in Python.
Is DeepSearcher free?: Yes. DeepSearcher is open source, so the software itself is free to use.
Can I self-host DeepSearcher?: Yes. DeepSearcher can be self-hosted on your own server or infrastructure.
What is DeepSearcher an alternative to?: DeepSearcher is an open-source alternative to Reason. Other open-source alternatives to Reason include LMMS and Ardour.
Is DeepSearcher actively maintained?: Yes. The most recent commit to DeepSearcher was on 22 September 2026. The project has 8.3k stars on GitHub.