Deep research · AI agent
Open Science: review, pricing, security and alternatives
Open Science is an open-source AI agent published by AIPOCH, in the deep research family. Open Science combines agents, MCP tools and Python or R execution in a desktop research workspace with traceable artifacts. Its repository has 5,355 stars and its last commit is from October 24, 2026.
What Open Science does
Open Science belongs to the deep research family: agents that search, read and cross-check dozens of sources to produce a sourced report. On our grid it ranks #3 of the 18 projects of this family listed in the directory.
You use it from: desktop app. Usable models: any OpenAI-compatible model. It can run on your own machine or server.
Who is Open Science for?
It targets analysts, students and teams who must cross-check many sources to produce a reasoned summary. Typical tasks people give it:
- write a sourced overview of a topic
- compare products or competitors
- prepare a technical or regulatory watch
It is a good candidate if your data must stay on your machines.
Access and human control
According to its documentation, Open Science can:
- read and edit files
We could not establish whether it asks for human approval before sensitive actions: test it first on an unimportant account or folder.
Open Science pricing
The code is free, under the Apache-2.0 licence.
Getting started with Open Science
- Install it: the project ships as a Node.js package (install with
npm, or run directly withnpx). The exact command is in the repository README. - Create an API key with the model provider and put it in an environment variable, never in a shared or versioned file.
- Give it a first playground with nothing at stake: a test folder, a secondary account or a throwaway project. Only open your real accounts once you have seen how it behaves.
- Give it a short, checkable task, review the result and its action log, then raise the difficulty step by step.
Security: risk level
An agent's report may cite misread or invented sources: check the links before reusing a figure.
Three habits: least privilege (minimal rights, dedicated keys), human approval for irreversible actions, a sandbox for code execution. The AI agent security check reviews your setup in a few minutes.
Project activity and releases
Created on July 3, 2026, the aipoch/open-science repository has 5,355 stars, 534 forks and 23 open issues, with 3,248 commits in total. It received changes this month.
Over the last 52 weeks: 3,242 commits, an average of 62.3 per week.
77 releases in total; 29 in the last twelve months. Latest release: v1.0.2, on October 22, 2026.
Open Science vs other deep research
GitHub stars of the best-rated open-source projects in the deep research family. Stars measure attention, not quality: a heavily promoted project collects them fast, a specialised tool will have few.
Open Science and other deep research at a glance
The 7 best-ranked agents in the same family, 7 of them open source. The score out of 100 only applies to open-source projects; for proprietary services we show the published entry price. A dash marks information the documentation does not state.
| Agent | Model | Score | Stars or entry price | Self-hostable | Human approval |
|---|---|---|---|---|---|
| Open Science | open source | 76 | 5.4K ★ | yes | – |
| DeerFlow | open source | 87 | 84.4K ★ | yes | – |
| GPT Researcher | open source | 80 | 30.3K ★ | yes | – |
| Feynman | open source | 74 | 10K ★ | yes | – |
| Local Deep Research | open source | 74 | 9.4K ★ | yes | – |
| OpenScience | open source | 70 | 4.2K ★ | yes | – |
| LLM for Zotero | open source | 68 | 3.4K ★ | yes | – |
| EvoScientist | open source | 65 | 4.9K ★ | – | – |
How we rated it
Score: 76/100, computed only from public, verifiable data, with no subjective testing or partnership:
- Adoption 21/40: 5,355 stars on a log scale (40 points from about 200,000).
- Activity 30/30: last commit less than a month ago, 29 releases in six months, 3,242 commits in a year.
- Framework 25/30: licence, default human approval, self-hosting, model choice and documentation site.
The score does not say whether the agent will succeed at your tasks: it measures how solid the project is. The full grid is on the method page.
Verdict
Open Science is a serious option; check the limitations below before granting it access.
Strengths
- Very active development
- Frequent releases (29 in a year)
- Can run on your side: data under control
- Free choice of model
- Permissive licence (Apache-2.0)
Alternatives
- DeerFlow84.4K ★
- GPT Researcher30.3K ★
- Feynman10K ★
- Local Deep Research9.4K ★
- OpenScience4.2K ★
- LLM for Zotero3.4K ★
Learn more
Frequently asked questions
Is Open Science free?
The software is free (Apache-2.0 licence). You still pay for the model calls, unless you use a local model.
Is Open Science safe?
Our risk level: low. Give it minimum rights and approve irreversible actions.
Which models does Open Science use?
According to its documentation: any OpenAI-compatible model.
Can Open Science be installed on your own server?
Yes, from the aipoch/open-science repository. Data then stays with you, but security and updates are your job.
What are the alternatives to Open Science?
In the same family: DeerFlow, GPT Researcher, Feynman, and Local Deep Research.
Open Science or DeerFlow: what is the difference?
Both belong to the deep research family. Open Science has 5.4K stars against 84.4K for DeerFlow. The right choice mostly depends on the access you are willing to give it.
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Neutrality. No affiliate links. No vendor pays to be reviewed, rated or ranked. Reviews are directed by François Chollet, neutral and factual, and every data point is dated and sourced. How we score