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Most AI interfaces are designed to generate text for people to read. Jev AI explores a different interface: typed decisions that software can use directly. Give it unstructured state—text, context, or JSON—and ask a concrete question. Jev AI organizes the result into a decision type such as: - Choice — select one option from a list - Noul — return a yes/no probability - Score — evaluate an input on an ordered scale
Hi Product Hunt 👋
I’m [your name], the maker behind Jev AI.
I built Jev AI after seeing how many software workflows still treat AI output as a paragraph that must be parsed, validated, and interpreted before anything can happen next.
Jev takes a different approach: ask one concrete, typed question and make the decision path visible. The Playground currently demonstrates three patterns:
- Choice for routing or selecting one option
- Noul for yes/no decisions with a probability
- Score for ordered ratings and thresholds
The result is designed to be easier to inspect and connect to a workflow: answer, probability or score, confidence, and next action.
This is an independent educational project, so the examples are intentionally transparent and illustrative. It is not trying to replace ChatGPT or every LLM use case. Jev is for bounded decisions where software needs a clear result and a sensible fallback when confidence is low.
Try the Playground here:
https://jev-ai.info/playground
I’d especially love feedback from developers building support routing, moderation, agent tool selection, risk scoring, or other automation that needs typed output.
What is the first decision in your product that you would want an AI system to return as a type instead of prose?
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About jev ai on Product Hunt
“Typed AI decisions for software workflows”
jev ai was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #135 on the daily leaderboard. Most AI interfaces are designed to generate text for people to read. Jev AI explores a different interface: typed decisions that software can use directly. Give it unstructured state—text, context, or JSON—and ask a concrete question. Jev AI organizes the result into a decision type such as: - Choice — select one option from a list - Noul — return a yes/no probability - Score — evaluate an input on an ordered scale
jev ai was featured in Productivity (661.3k followers), SaaS (44.4k followers) and Modeling (476 followers) on Product Hunt. Together, these topics include over 219.3k products, making this a competitive space to launch in.
Who hunted jev ai?
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