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jev ai
Typed AI decisions for software workflows
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
Top comment
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?
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
On the analytics side, jev ai competes within Productivity, SaaS and Modeling — topics that collectively have 706.1k followers on Product Hunt. The dashboard above tracks how jev ai performed against the three products that launched closest to it on the same day.
Who hunted jev ai?
jev ai was hunted by ly love. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of jev ai including community comment highlights and product details, visit the product overview.