ai-berkshire
An AI-powered multi-agent parallel research framework providing professional-grade investment decision support.
- Region
- Domestic
- Pricing
- Free
- Open source
- Yes
- GitHub Stars
- ★ 4.0k
- Views
- 13
- Source
- GitHub
- Added
- 2026-06-28
- Last verified
- 2026-06-28
Overview
AI Berkshire is a skill suite for investment research compatible with Claude Code and Codex, systematically and structurally integrating the value investing methodologies of Warren Buffett, Charlie Munger, Dong Yongping, and Li Lu. Through parallel multi-agent research, it enables professional-level investment analysis. The framework includes multiple bias-prevention mechanisms and precise calculation tools to ensure rigor and reproducibility in research outcomes. Suitable for individual investors and teams, it helps users conduct deep investment analysis and informed decision-making.
Key features
- ▪Multi-agent parallel research
- ▪Integration of four master investors' methodologies
- ▪Forces clear conclusions—no ambiguity
- ▪Structured anti-bias mechanisms
- ▪Precise financial data computation
Use cases
Pros
- ＋Multi-perspective adversarial analysis
- ＋Reproducible research workflow
- ＋High data accuracy
- ＋Well-suited for team collaboration
Limitations / notes
- －Requires internet connection
- －Higher learning curve
Who it's for
This overview was compiled by AI from public sources and may contain inaccuracies — please refer to the official site.
FAQ
Is it free?
The project is open source, but specific usage may incur API costs.
Do I need scientific internet access?
Some features may require access to foreign websites; using scientific internet access is recommended.
Does it support Chinese?
Yes, both documentation and output are available in Chinese.
Can it be used commercially?
Yes, it can be used commercially, but must comply with relevant open-source licenses.
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