Jev case: Is Jarvis finally here?
Described Jev as an API for structured decisions used to route models, rank results, and check LLM outputs without a chatbot.
The original post
Is Jarvis finally here?
TypeSafe just launched Jev, an API for structured decisions that can route models, rank search results and check other AI systems WITHOUT a chatbot in the loop.
Imagine a Magic 8-Ball that actually works: a typed answer, with odds and a confidence score.
This means they can:
• Model routing: send each request to the right mode
• LLM output checks: flag weak answers for review before users see them
• Support workflows: sort tickets and decide which to automate or escalate
And just realized TypeSafe reports ~150ms latency, ~100x lower cost & faster responses than LLMs.
Early API access waitlist is open below.
Quoted post
@CompleteSkeptic34.6M viewssourceAfter co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not led to AGI? I’ve spent the last 2 years in stealth building a new way to train models (RLCD), and a new type of frontier AI model that we are releasing today: Jev • 20-200x faster • 40-400x
Engagement when collected
Numbers are a snapshot taken from X when the case was added to the library (schema v1, collected 2026-09-19); they will not match today.
Where this case fits
Filed under agents & workflows, coding & developer tools, support & operations. In the pattern Jev is built for, the model answers a bounded question per step — and ordinary code acts on the answer, because the answer is already a value rather than a paragraph. Other posts in the same family are on the agents & workflows page.
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Last updated: 2026-09-22 · sources & corrections · every card links to its author's original post