FEDRO on X: "As the first System One model from @typesafeai, Jev is designed to make fast, structured decisions directly inside software. Instead of asking an AI to generate text and then writing additional code to parse the response, Jev takes a different approach: → Send your application state → Ask a typed question → Get a typed decision back → Receive probability and confidence alongside the result No JSON prompting. No messy output parsing. Just structured decisions your application can use immediately. Jev evaluates three types of questions in parallel: 🔹 Choice — select between defined options 🔹 Score — evaluate something against a scoring framework 🔹 Noul — handle structured decision questions designed for application logic Speed is another major part of the design. Jev can respond in roughly 70–500ms, making it suitable for situations where an AI decision needs to happen inside an active software workflow rather than after a long generation process. And the pricing is built around high-volume inference: 💰 $0.042 per million input tokens 🆓 Output tokens are free That opens up interesting use cases across software infrastructure, including: 🎫 Ticket routing Automatically determine where an incoming support request should go. 🛡️ Moderation Make structured moderation decisions based on application state and predefined questions. 📊 Risk scoring Evaluate transactions, users, or events and return structured scores with confidence. 🤖 Agent branching Let an AI agent decide which tool, workflow, or next step should execute. The key idea is simple: Traditional LLM workflows often look like: Prompt → Text → Parse → Validate → Application logic Jev is designed more like: Application state → Typed question → Typed decision That difference can matter when AI isn’t being used to write something for a human, but to make a small, fast decision that software needs to act on. And now Jev is available through the https://t.co/toijCbney0 API. You can access it using: Jev-1.13.0 or Jev-Latest For developers building AI-powered applications, agents, automation systems, and decision pipelines, this is an interesting shift toward treating AI as a structured decision layer inside software. Try it here: https://t.co/ppprVoKA22 Learn more in the https://t.co/toijCbney0 LLM Service documentation. @justinsuntron @BAI_AGI #TRONEcoStar"

FEDRO

@thenameisfedro

As the first System One model from @typesafeai, Jev is designed to make fast, structured decisions directly inside software. Instead of asking an AI to generate text and then writing additional code to parse the response, Jev takes a different approach: → Send your application state → Ask a typed question → Get a typed decision back → Receive probability and confidence alongside the result No JSON prompting. No messy output parsing. Just structured decisions your application can use immediately. Jev evaluates three types of questions in parallel: 🔹 Choice — select between defined options 🔹 Score — evaluate something against a scoring framework 🔹 Noul — handle structured decision questions designed for application logic Speed is another major part of the design. Jev can respond in roughly 70–500ms, making it suitable for situations where an AI decision needs to happen inside an active software workflow rather than after a long generation process. And the pricing is built around high-volume inference: 💰 $0.042 per million input tokens 🆓 Output tokens are free That opens up interesting use cases across software infrastructure, including: 🎫 Ticket routing Automatically determine where an incoming support request should go. 🛡️ Moderation Make structured moderation decisions based on application state and predefined questions. 📊 Risk scoring Evaluate transactions, users, or events and return structured scores with confidence. 🤖 Agent branching Let an AI agent decide which tool, workflow, or next step should execute. The key idea is simple: Traditional LLM workflows often look like: Prompt → Text → Parse → Validate → Application logic Jev is designed more like: Application state → Typed question → Typed decision That difference can matter when AI isn’t being used to write something for a human, but to make a small, fast decision that software needs to act on. And now Jev is available through the B.AI API. You can access it using: Jev-1.13.0 or Jev-Latest For developers building AI-powered applications, agents, automation systems, and decision pipelines, this is an interesting shift toward treating AI as a structured decision layer inside software. Try it here: chat.b.ai/chat Learn more in the B.AI LLM Service documentation. @justinsuntron @BAI_AGI #TRONEcoStar

B.AI

6:22 PM · Sep 23, 2026·

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