Effi Flo Report
Jev vs LLM for Recruiting Workflows
What Jev is, how it differs from other LLMs, and why you should seriously consider it for your recruiting workflows. We ran it across 6 everyday recruiting use cases; here’s the research and a practical guide to using it.
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Updated September 2026
What you will find inside
- What makes Jev different from the LLMs you're already using
- Where Jev could actually fit into a recruiting workflow
- Why it's worth paying attention to for recruiting use cases
- What happened when we put Jev through 6 real recruiting use cases
- A practical guide to using Jev in your own workflows
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FAQ
Frequently Asked Questions
What is Jev?
Jev is a fast judgment model, released in September 2026 by Diogo Almeida's team. It answers from a known list of options: it picks one option, places an item on a scale, or answers yes or no, in under a second, and every answer comes with a confidence score. It never writes free text, so there is nothing to parse.
When should recruiters use plain code, Jev, or a reasoning LLM?
Ask two questions. Is it a fact or a sum (location, dates, years of experience, cut-off rules)? Use plain code. Do you know the possible answers? Use Jev. If the answer is open (summaries, explanations, outreach, research with many steps), use a reasoning LLM.
How should a recruiting team start with Jev?
Start with one call, not the whole process: pick one yes/no call you send to a big LLM today, write the answer options first, run it next to your current process and compare. Act alone only on high confidence and send the middle to a recruiter. Cut-offs live in code, and no model rejects a person on its own.