Continual learning for AI teams

Models that keep learning.

Every user interaction trains the model driving your agent. Quality keeps climbing, latency and cost keep falling, and you own the flywheel.

The harness is not enough.
Neither is the model.

Today’s agents are a frozen model with a notepad. They write down what they learn and reread it on every task, like Leonard in Memento. When the model learns inside its harness, what it writes down becomes what it knows.

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Backed by

  • Y Combinator
  • A.Capital
  • SignalFire
  • Microsoft M12
  • Samsung Next
  • Essence VC
  • Clem DelangueCEO, Hugging Face
  • Lasse EspeholtCTO, Ineffable Intelligence
  • Charlie SonghurstBoard director, Meta
  • Arash FerdowsiCTO, Dropbox
  • Zehan WangHead of AI Research, Twitter
  • Saturnin PugnetFounder, Worldcoin
  • Bob van LuijtCEO, Weaviate
  • Philip RathleCTO, Neo4j

Blog

DatePostRead
Sep 2026
Why we built Continual-ARC.
15 min
Aug 2026
The harness is not enough.
4 min