AutoResearchClaw
Fully autonomous & self-evolving research from idea to paper. Chat an Idea. Get a Paper. 🦞
The Lens
By Erik Loyd, SaaS CEO and former COO/CFO of an AWS Premier Partner.
Updated Jun 2026
AutoResearchClaw automates research by letting AI agents search, analyze, and synthesize information from multiple sources, then compile structured reports on the results. You give it an idea, it designs experiments, runs them, writes the paper, and iterates on the results. Basically a research assistant that never sleeps.
It's built for academic and ML research specifically, not general-purpose AI automation. The pipeline handles literature review, experiment design, code generation, result analysis, and paper writing in a loop.
The catch: this is bleeding edge. growing fast, but it's a research tool built by a research lab. The output still needs human review; don't submit a paper without reading it. And the quality depends heavily on the underlying LLM you point it at.
Free vs Self-Hosted vs Paid
fully freeFully open source under MIT. No paid tier, no hosted version, no account needed. You clone the repo and run it with your own LLM API keys. The only cost is the API calls to whatever model you use (Claude, GPT, etc.), which can add up during iterative research runs.
Free to use, pay only for the LLM API calls you make.
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A low score is not a verdict on quality. Young and niche tools start low by design. How we calculate scores
Trust Signals
License: MIT License
Use freely, including commercial. Just keep the license.
Commercial use: ✓ Yes
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