Research & Data Visualization Platform, Build a Directory or Searchable Tool

Co-op Atlas: AI-Powered Global Co-op Law Map & Repository

Client: JNF Digital (self‑initiated R&D) Year: 2025 Industry: legal, international development; civic tech, research

Built an AI-driven platform that ingests, summarizes, and visualizes global cooperative law documents for interactive exploration and comparison.

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Project Overview

Centralized global cooperative law documents into an AI-powered mapping and directory platform, enabling instant browsing, filtering, and comparative analysis via interactive AI-summarized visualizations.

The Challenge

  • Scattered, unstructured, multilingual PDFs made comparing and analyzing cooperative laws slow, error prone, and expensive. Co-op Atlas ingests these documents into a single AI enhanced repository, auto summarizes statutes, and visualizes them on interactive maps for rapid, plain language insights.

Our Approach & Key Contributions

Advanced Ingestion Pipeline

Implemented OCR and multilingual parsing to ingest scanned PDFs into a Postgres datastore.

OCRTesseract.jsPDF.jsPostgreSQL

AI Layer Integration

Integrated OpenAI GPT‑4o to auto-summarize statutes, answer contextual questions, and flag governance requirements.

OpenAI GPT-4oPrompt Engineering

Interactive Mapping and Visualization

Developed a responsive interactive map and data visualization tools using React 18, Mapbox GL, and Recharts to reveal geographic and temporal trends.

ReactMapbox GLRecharts

Tools & Technologies

ReactTypeScriptTailwindCSSShadcn UIMapbox GLRechartsViteNode.js/ExpressPostgreSQL/SupabasePDF.jsTesseract.js OCROpenAI GPT-4o

Outcomes & Results

Released public beta covering 72 countries and 200+ statutes with <3.5s AI response time

researchers can compare governance requirements side-by-side, export data, and submit new laws via contributor workflow.

Key Metrics

Documents processed — 203; Countries represented — 72; Regions covered — 7; Avg. AI answer latency — 3.2 s; Token-usage optimisation — 40% reduction via context caching

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