CONTROLAgents & automation
Jev: Fast Decision-Making for Agentic Systems
Elias Andualem@eandualem
0:41Jev is a new System One model from TypeSafe AI designed to accelerate decision-making in agentic systems by processing state and typed questions to produce calibrated decisions in under a second, eliminating the need for text parsing.
Pattern↑ Jev AI decision models
Decision speed in agentic systems, shown on a robot.
In agentic systems, a lot of the work is turning semantic understanding into decisions: which pipeline, act now or wait, stop or continue. Doing that with an LLM works, but each decision costs seconds, and those seconds land in front of everything else.
Jev, the new System One model from TypeSafe AI, is built for that layer. State and typed questions in, calibrated decisions out in well under a second. No text to parse.
Charlie is the demo: a 3D robot in a browser voice call. GPT-Live carries the conversation and only talks. A separate model decides what the body does, and that model was the latency: 3 to 6 seconds between the words and the movement, never in sync.
With Jev as the decision layer, it answers eight typed questions on every fragment of speech in one call, while I am still talking. The body starts about half a second after the words, often before the sentence ends.
Jev is early access.
Avatar Studio: github.com/eandualem/avatar-studio
Jev: typesafe.ai
#Jev #TypeSafeAI #AgenticAI #AIAgents #DecisionModels #OpenSource @typesafeai