Decision models like Jev return a probability for every allowed answer instead of generating text, which makes them much faster and cheaper than asking a large language model.
I break down how Jev, OpenAI’s Decisions API, Cloudflare’s Clef and the open-source Kev score a question in one pass. Then I rebuild a production check in Mastra: picking the threshold with an eval, handling wrong answers and refusals with ClassifierProcessor, and switching providers without rewriting the logic.
This video is a paid partnership with Mastra.
Work with me
Need senior technical guidance?
As a fractional CTO, I help teams make confident architecture and AI integration decisions.




