Fatih Yildiz says TypeSafe AI's Jev looks promising for observability decision model use cases, noting latency adds up when using frontier models at edge_delta for operational priority scoring and event routing, and is testing Jev.
#Jev from @typesafeai looks very promising for Observability Decision Model use cases. At @edge_delta , we use frontier models for operational priority scoring, routing events, identifying recurring issues, and similar decisions. Latency adds up. I tested Jev on our
The author tested Jev on a benchmark of 1,565 German and English business emails from industrial suppliers across 10 categories, finding it less accurate than Gemini, but focused on where the errors occurred and still plans to put it into production.
Aaron Levie says Jev helps agents make split-second decisions in workflows, data classification, and judgment calls, with a Box and Jev demo pulling an incident report from Box.
A user shares JEV processing 100 fictional interview minutes: sorting Pass/Hold/Pass, scoring skills, communication and motivation, and flagging major concerns in 12.8 seconds for $0.005 total.
