license: cc-by-4.0
language:
- en
tags:
- government
- documents
- OCR
- parse
- reducto
pretty_name: UFOCR
size_categories:
- n<1K
UFOCR: Declassified UFO/UAP Documents Parsed with Reducto
UFOCR is an open dataset of the FBI's and U.S. Department of War's declassified records on UFOs, UAPs (unidentified aerial phenomena), and extraterrestrial investigations — fully parsed into clean, structured, LLM-ready text using Reducto.
The original government archives are a notoriously difficult OCR challenge: scanned typewriter pages, faded carbon copies, handwritten margin notes, redacted blocks, rotated scans, multi-column memos, and dense tables. UFOCR is what those documents look like after being run through a modern document parsing pipeline built for exactly this kind of mess.
About the Dataset
- Source: Public declassification releases from the FBI Vault and the Department of War UFO Archive
- Content: All documents and images from both collections, parsed end-to-end
- Format: Structured text + layout metadata, ready for retrieval-augmented generation (RAG), fine-tuning, search indexing, or analysis
- License: CC BY 4.0 — free to use commercially with attribution
- Language: English
Why this dataset exists
Declassified government archives are some of the highest-friction documents on the public internet. The raw PDFs are technically "available," but practically unreadable at scale — you can't grep across thousands of scanned typewriter pages, and naive OCR mangles tables, redactions, and handwriting badly enough to make downstream LLM work unreliable.
We released UFOCR to (1) make a culturally interesting corpus actually usable for AI research and journalism, and (2) demonstrate what high-accuracy document parsing looks like on real-world worst-case inputs.
How it was built: parsing with Reducto
Reducto is a document ingestion and parsing API used by AI teams at companies like Harvey, Scale AI, Vanta, and Toast to turn complex PDFs, scans, spreadsheets, and slides into LLM-ready structured data.
Every page of the FBI and DoW UFO archives was processed through Reducto's parsing pipeline, which combines:
- Layout-aware computer vision to detect regions, tables, figures, and reading order on each page
- Vision-language models (VLMs) that interpret each region in context — linking labels to values, reading handwriting, and preserving table structure
- Agentic OCR that reviews its own outputs in real time and corrects mistakes before producing the final result
The result is parsed text that preserves the structure of the original documents — including tables, multi-column layouts, handwritten annotations, and bounding box metadata — instead of the flat, garbled string you typically get from off-the-shelf OCR.
If you see any mistakes or documents with incorrect parsing, reach out to the team at support@reducto.ai to flag.
Use cases
- RAG over declassified archives — build chatbots and research tools grounded in primary government sources
- Fine-tuning and pretraining — high-quality OCR'd English text from a unique domain
- Historical and journalistic research — full-text search across decades of UFO/UAP investigations
- Benchmarking OCR and document AI systems — the FBI/DoW corpus is a brutal stress test for any parsing pipeline
Try Reducto on your own documents
If you have your own difficult documents — financial filings, medical records, insurance forms, legal contracts, scanned archives, multilingual scans, handwritten notes — Reducto handles them through a single API. The platform supports PDFs, images, spreadsheets, and slides across 100+ languages, with SOC 2 and HIPAA compliance and self-hosted deployment options for regulated industries.
Get started:
- Explore the product: reducto.ai
- Talk to our team: reducto.ai/contact