Beyond-frontier consistency, at Haiku-class cost. Your agent gets more reliable the longer it runs — no fine-tuning, nothing new to host.
Hour two of any serious agent session, even the best models start forgetting what they were told, repeating bugs they just fixed, abandoning the user's plan.
Bigger context windows don't fix this. Bigger models don't fix this — they just make the bill worse.
ActiveMem catches the moment your agent is about to repeat a known mistake — and corrects it in flight, before it derails the session. Hour two looks like minute one.
It plugs into the deployment you already have, and gets sharper with every session. No retraining. No datasets. Nothing new to host.
The hard part of shipping agents isn't raw capability — it's keeping them consistent once they're loose in the real world. ActiveMem closes that gap, so a lean, low-cost model holds the line like a top-tier one, run after run.
Now in private beta. Benchmarks publishing soon.