The post explains that Jev is not another chatbot but is built to choose, score and route, while an LLM drafts, summarizes and converses. In a clinic, the LLM handles language, Jev checks or routes the output, and staff stays in control.
Jev is not another chatbot. It is built to choose, score and route; an LLM is built to draft, summarize and converse. For a clinic, the useful pattern may be both: the LLM handles language, Jev checks or routes the output, and staff stays in control.
During live clinical consultations, an ambient scribe periodically feeds transcripts to Jev, which traverses a medical ontology to classify symptoms, update the differential diagnosis, suggest treatments, and flag red flags in real time.
The author demonstrates how to triage a patient to the right doctor using only TypeSafe AI's Jev model and some question-asking code, noting that no LLM is used during the conversation.
A developer shares building a calorie tracking app with Jev, highlighting its instant experience.
