Turn any document dump into a searchable evidence database.

Built by the team behind epstein-data.com — where we turned the 218GB DOJ Epstein file release into a fully searchable, entity-linked, citation-backed research database.

This project is licensed under PolyForm Noncommercial License 1.0.0.

• Noncommercial use is allowed under the terms in LICENSE.
• Commercial use requires a separate commercial license from the project owner.
• Required attribution notice is in NOTICE.
• Third-party dependency notices are in THIRD_PARTY_NOTICES.md.

pip install -e ".[pymupdf,nlp]"
python -m spacy download en_core_web_sm

# Point at a folder of PDFs, get a searchable database
casestack ingest ./my-documents --name "City Council FOIA"
# Serve it locally
casestack serve
# Check status
casestack status

Copy case.yaml.example to case.yaml and customize. See the example for all options.

1. OCR — Extract text from PDFs (Docling or PyMuPDF)
2. Entity Extraction — Find people, orgs, dates, money, phone numbers (spaCy NER)
3. Deduplication — Identify duplicate documents (content hash + fuzzy matching)
4. Export — SQLite database with FTS5 full-text search
5. Serve — Datasette web interface with search, filtering, and AI Q&A

Pre-configured case files for known document sets:

• presets/epstein.yaml — DOJ Jeffrey Epstein File Release (218GB, 1.38M PDFs)