ESG Analytics
ESG Data Extraction Pipeline
NLP-driven extraction of sustainability indicators from heterogeneous corporate reports at scale.
About this project
Sustainable-finance analysts spent 60–80% of their time hunting ESG metrics across PDFs of vastly different shapes — annual reports, sustainability reports, regulatory filings — with no consistent terminology.
Solution
Built a document-understanding pipeline combining layout parsing, semantic chunking, and LLM-based extraction with strict schema enforcement and human-in-the-loop review for low-confidence rows.
Technology
- Python
- LangChain
- PostgreSQL
- Tesseract
- GPT-4
- FastAPI
Impact
Cut analyst extraction time by 75%, expanded coverage from ~150 to ~3,000 issuers, and provided audit trails per data point for compliance.