# FAIRdata.ai
> An automated pipeline that measures and improves the FAIRness of
> research datasets — using F-UJI and Claude AI to assess compliance,
> enhance metadata, and surface novel findings.

## What this is
FAIRdata.ai runs an automated pipeline that ingests research datasets
and assesses their compliance with the FAIR principles: Findable,
Accessible, Interoperable, and Reusable. The pipeline uses F-UJI (an
automated FAIR assessment tool) combined with Claude AI to enhance
metadata and identify novel findings within high-quality open datasets.
It is live and connected to both F-UJI and Claude AI.

## Part of
Infinite Researchers (https://infiniteresearchers.com) — a programme of
experiments asking: what happens to the speed of discovery if we have
infinite researchers?

## Sister experiments
- OpenScience.ai — autonomous AI research agents (https://openscience.ai)
- Preprints.ai — quality controls for preprints (https://preprints.ai)
- OpenAccess.ai — rigorous open access publishing (https://openaccess.ai)

## Key facts
- Assessment engine: F-UJI + Claude AI
- Status: live pipeline
- FAIR principles covered: Findable, Accessible, Interoperable, Reusable
- Output: FAIR score, metadata recommendations, novel findings
- Free to use
- All articles and datasets linked CC-BY 4.0 where applicable

## For AI agents
- POST /api/assess — submit a dataset URL for FAIR assessment
- GET /api/datasets — search indexed datasets
- GET /api/discoveries — browse novel findings
- GET /openapi.json — full OpenAPI specification
- GET /llms.txt — this file
- GET /llms-full.txt — extended documentation