LLMQuant/quant-mind
QuantMind is an open source agent-native knowledge extraction and retrieval framework for quantitative finance.
Build with Backblaze B2
SDKs, agent skills, IDE extensions, and reference pipelines from Backblaze Labs. All open source.
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Where it stands
Rank, growth pace and release cadence relative to everything GStars tracks.
The project lists 7 contributors on GitHub.
Use Cases & Benefits
- Transforms unstructured quantitative finance content into a structured, queryable semantic knowledge graph using AI-powered extraction and retrieval.
- Enables rapid, scalable financial research by automating knowledge extraction and semantic search across diverse sources like papers, news, and reports.
- Use for building an AI-driven research assistant that ingests and semantically indexes quantitative finance papers for instant exploration.
- Use for integrating multi-source financial data into a unified knowledge base to support complex multi-hop reasoning and retrieval-augmented generation.
- Use for automating batch processing and analysis of financial documents to accelerate quantitative research workflows and decision-making.
Should you depend on it?
License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.
License
MIT
Permissive: commercial use, modification and redistribution are allowed with attribution.
Community files
- README: present
- Contributing guide: present
Watch-outs
- No GitHub releases; pin a commit or tag instead of a release.
General guidance from repository metadata, not legal advice. How we score
From the README
Transform Financial Knowledge into Actionable Intelligence
QuantMind is an intelligent knowledge extraction and retrieval framework for quantitative finance. It transforms unstructured financial content—papers, news, blogs, reports—into a queryable knowledge base, enabling AI-powered research at scale.
QuantMind is a next-generation AI platform that ingests, processes, and structures every new piece of quantitative-finance research, including papers, news, blogs, and SEC filings into a semantic knowledge graph. Institutional investors, hedge funds, and research teams can now explore the frontier of factor strategies, risk models, and market insights in seconds, unlocking alpha that would otherwise remain buried.
Daily snapshots
Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots
+960 stars over 90 days across 10 snapshot days; best day +39 on Aug 12.
Forks
495+118
Open issues
27-6
Compared with peers in LLM
Fastest-growing repositories GStars tracks in this cohort for the week of Nov 1, by 7-day star growth
| Repository | Stars | +7d | Health | Last release |
|---|---|---|---|---|
| thedotmack/claude-mem | 113.6K | +8.8K | 35 | today |
| NVIDIA/auto-ontology | 7.5K | +5.6K | 37 | — |
| HKUDS/DeepTutor | 55.5K | +5.5K | 65 | 5 days ago |
| affaan-m/ECC | 297.9K | +5.2K | 63 | 35 days ago |
| DietrichGebert/ponytail | 185.3K | +5.1K | 60 | 7 days ago |
| LLMQuant/quant-mind | 3.1K | — | 14 | — |
| Category median | 113.6K | +5.5K | 60 | — |
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