DETECTAgents & automation
JEV for Construction Data Analysis
Kenny Shultz@PermitZIPhvac
3:05JEV is a small, fast model designed to answer structured questions about data, such as yes/no, scores, or selections from a list, making it efficient for analyzing project data like meeting transcripts.
TakeIt's a small, fast model that answers structured questions about data: yes/no, a score, or a pick from a list.
Pattern↑ State to typed decisions for software
Quick JEV explainer for people in construction who aren't computer scientists.
JEV (by @typesafeai) isn't an LLM. It's a small, fast model that answers structured questions about data: yes/no, a score, or a pick from a list.
You give it a meeting transcript and ask "Was electrical scope discussed?" and it just tells you.
At @PermitZIP, we've given an "ask_jev" tool to our agent harness. Instead of the LLM reading billions of tokens of project data (hundreds of dollars to do so), the agent writes the questions and lets JEV do the reading.
JEV is fast and cheap enough to feel practically free next to frontier-model token costs.
The video walks through a real example on our own meeting transcripts.
I realize this sounds sponsored, but it's not. You can tell I don't really know much about the technical part of this because I only learned how to pronounce "noul" today....AFTER this video. 🫥
Related builds
Vectorless RAG with Jev
This project introduces a novel approach to Retrieval Augmented Generation (RAG) that replaces traditional embedding methods with a structured, table-of-contents-based navigation system, significantly improving speed and reducing costs by offloading non-generative tasks to Jev.
