How Pulsar works

1. Collection

   Every morning Pulsar reads GitHub (recent repositories gaining stars), Hacker News Show HN, Reddit (r/selfhosted, r/SideProject, r/LocalLLaMA, r/opensource), Product Hunt, Lobsters and new awesome-selfhosted entries.

2. Signal

   Each candidate gets a score: stars gained per day, points and comments, presence on several sources. Duplicates merge: one repository seen on GitHub and Hacker News becomes a single entry.

3. Reading

   A language model classifies each tool (self-hosted, SaaS, desktop, command line, library), its price and the role of AI, then summarises it in French and English from the collected data only.

4. Selection

   The best scores make the issue, with a floor per family so self-hosted software, online services and developer tools all appear.

5. Writing

   The model writes the headline and introduction and picks the gem of the day. When no model answers, a template takes over: the issue still ships.

The colour code

Each entry carries three blocks: the kind of software, its pricing model, and a magenta block when AI is at the core of the product.

• Self-hosted
• SaaS
• Desktop
• Mobile
• Command line
• Library

• Open source
• Free
• Freemium
• Paid
• AI

Language models

Pulsar can talk to a Claude Code subscription, a Codex subscription, the OpenAI API, and any OpenAI-compatible service such as a local model. They are tried in order, the next one stepping in on failure.

Connected today : none yet.

By the numbers

1 issues, 1,384 tools described, 1,528 candidates scanned, 25 of them with AI at the core.