head to head · open source
Automatisch vs local-deep-research
Automatisch has 13,975 GitHub stars, 1,064 forks, 287 open issues and last shipped 7 months ago. local-deep-research has 9,109 stars, 824 forks, 889 open issues and last shipped yesterday. Automatisch leads on adoption by 53% (13,975 vs 9,109 stars). Automatisch is written in JavaScript under a custom or non-standard licence; local-deep-research is written in Python under MIT. Automatisch has attracted 8% as many forks as stars, local-deep-research 9%. local-deep-research was the more recently maintained of the two, and both are self-hostable with no licence fee.
Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.
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Side by side
| Automatisch | local-deep-research | |
|---|---|---|
| GitHub stars | ★ 14K | ★ 9.1K |
| License | Custom / other | MIT |
| Written in | JavaScript | Python |
| Last push | 2026-02-11 | 2026-09-19 |
| Forks | ⑂ 1.1K | ⑂ 824 |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick Automatisch if
- You weight community size — 14K stars and counting
- You want the Custom / other license terms
- Your stack matches JavaScript
- You value the larger contributor base for long-term maintenance
pick local-deep-research if
- You want the local-deep-research feature set and don't need the biggest community
- You prefer the MIT license terms
- Your stack matches Python
- You evaluated both and local-deep-research fits your workflow better
About Automatisch
Automatisch is an open source integration platform for workflow automation, positioned as an alternative to Zapier. It lives in the JavaScript, low code, no code, self hosted, and automation ecosystem, and it is categorized under Productivity & Utilities / Automation. The project lets users connect services such as Twitter and Slack so that business processes can be automated without writing code.
read the full Automatisch overview →
About local-deep-research
Local Deep Research is an MIT licensed, Python based AI research assistant that performs deep, agentic research with proper citations across any local or cloud LLM and more than ten search engines, built for researchers, developers, and privacy conscious self hosters who want both the workload and the data to stay on hardware they control.
read the full local-deep-research overview →
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Frequently asked questions
Is Automatisch or local-deep-research more popular?
Automatisch has 13,975 GitHub stars and local-deep-research has 9,109. Automatisch has the larger community by that measure.
Are Automatisch and local-deep-research free?
Both are open source. Automatisch has no licence declared in this registry, and local-deep-research is licensed under MIT. Both are free to self-host.
What is the difference between Automatisch and local-deep-research?
Automatisch is written in JavaScript and local-deep-research in Python. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.
Which should I choose, Automatisch or local-deep-research?
Choose Automatisch if you want the larger community (13,975 stars) or its Custom / other licence terms. Choose local-deep-research if its feature set, stack or MIT licence fits better. Both are self-hostable.