LoreonLabs

Documentation

The Attention Engine

How LoreonLabs turns raw, live signals into a single, comparable read on what's gaining attention — computed entirely from real data.

What it does

The attention engine ingests live signals from every connected source, normalizes them into a shared model, and ranks what is accelerating. It never invents numbers — every figure traces back to a real source.

Inputs

  • Market data — prices, market cap, and 24h/7d/30d change.
  • Developer activity — commits, contributors, stars, and recency.
  • News & social — articles across crypto and tech feeds plus developer forums.
  • Web extraction — official sites, docs, and changelogs.

From signal to intelligence

  • Ingest live data from each source.
  • Normalize into narratives, builders, projects, ecosystems, and markets.
  • Correlate entities to the themes and ecosystems they belong to.
  • Rank by a concrete, real metric per surface.
  • Surface the result, with provenance on every item.

Weighted toward acceleration

The engine favors momentum over size: a small project moving fast can outrank a large but flat one. The exact metric for each surface is documented in its ranking page.