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Mobrief AI intelligence
Mobrief

Transparency

Method

How Mobrief collects and presents AI intelligence.

Every thread starts from source feeds, is normalized into a story record, and is published with direct receipts. The goal is not maximum volume. The goal is a cleaner operating picture.

What’s automated

  • Collecting new items from RSS/Atom feeds.
  • Scraping selected HTML sources when they publish without a feed and robots.txt allows it.
  • Normalizing, ranking, and clustering related coverage into thread-like rows.
  • Generating a static site and JSON indexes for search, browse, and saved state.
  • Generating structured summaries through a configured Claude CLI summarizer when enabled.
  • Publishing from a local cron job instead of GitHub Actions.

How the product is structured

  • Homepage: a briefing surface with clear editorial hierarchy.
  • Browse: the searchable archive and reference layer.
  • Story pages: dossier pages with summary, trust context, and receipts side by side.
  • Simple and Deep: one product, two levels of depth, not two disconnected experiences.

What we avoid

  • Copying entire articles. We link out and summarize.
  • Hype-first coverage. We down-rank fluff, customer-story wrappers, newsletter roundups, and low-context community noise.
  • Unlabeled speculation. If we infer, we should say so.

Source health

Last run: Apr 12, 2026 at 8:36 PM UTC • Sources OK: 80 / 82 • Quiet: 2 • Failed: 0

See fetch status JSON

  • Google Gemma Releases: None
  • Cohere Blog: None