Jev is having a moment. Every platform rushed to host it the same way: another model endpoint in the catalog, and good luck wiring it into your agent loop yourself. We took a different route at DigitalOcean. In addition to Jev being available in our Inference engine, Jev is also available inside Action Gateway as a first-class classifier tool, right next to browser automation, and 16,000+ other tools behind one governed MCP endpoint. That distinction sounds small. It isn't. Treat Jev as a model and your agent's LLM has to know about a second inference provider, manage another API key, and hand-roll the request plumbing. Treat it as a tool and any harness you already run (Codex, Claude Code, LangGraph) just discovers it and calls it, same as any other tool in the belt. Ask typed questions: a yes/no, a choice from your own list, a score on your own scale. Get back decisions with calibrated probabilities, schema conformance guaranteed. Answers land as data your code uses directly, so agents route, filter, and escalate without parsing prose. The gateway part matters too. Jev calls ride the same governance as everything else: scoped permissions, credentials that never enter the model context, low-confidence answers flagged for a human, every decision in the audit trail. We ran a Codex agent through it this week. One YAML, one prompt, and it turned a day of X noise into a shortlist worth reading, with the uncertainty left visible. If you want raw inference, Jev is on Serverless Inference too, at $42 per billion input tokens with output free. But agents shouldn't have to treat a classifier like a chatbot. Models reason. Jev decides. Ship both. On the same platform.