Jev turns a single agent chain into a self-rerouting decision graph
Jev acts as a control layer deciding which routes stay alive, which specialist takes over, when branches merge and when to stop, with a demo run reaching a 0.93 goal score at $0.020 decision cost.
jev engineering turns one agent chain into a decision graph that can reroute itself, and moves the expensive model out of every decision loop. the important part in this setup isn't the number of agents. it's that execution doesn't follow one fixed path anymore. up to 193x faster and ~445x cheaper on their published benchmarks (i've seen 444x quoted elsewhere too, the multiple moves around depending on the case, that's normal for this kind of number). every result can change what happens next: state → jev decision → branch → specialist agent → result → score → reroute jev sits above that graph deciding: → which route stays alive → which specialist gets control → when two branches should merge → when a result needs another pass → when the goal is good enough to stop one demo run, their numbers, not an independent benchmark: 5,400 executions → 0.93 goal score → $0.020 decision cost fine print because i couldn't independently verify that specific run — treat it as a demo, not a citation. the published 193x/445x figures are theirs too, same caveat as always with vendor benchmarks. that's why jev engineering is more than model routing. it's a control layer that keeps a changing agent graph pointed at one objective, instead of one expensive model babysitting every fork by itself. full breakdown below ↓