We built NabavkiData to automatically analyze 15,000+ government tenders in North Macedonia using 50+ risk indicators based on World Bank, OECD, and Ukraine's Dozorro methodology.

  The system flags: single-bidder tenders (specs written for one company), repeat winners, price anomalies, bid clustering, connected companies,
   and specification rigging.

  Tech stack: Next.js, FastAPI, PostgreSQL, Scrapy + Playwright for scraping, Gemini embeddings for semantic search, Python ML pipeline with
  150+ features.

  We scrape e-nabavki.gov.mk (the official procurement portal), extract PDFs with OCR, generate embeddings, and run risk scoring. Already used
  by 4,500+ companies and citizens.

  The corruption detection is the interesting part - we use materialized views to pre-compute risk scores across 8 flag types, then combine them
   into an overall risk rating. Happy to answer any technical questions.