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Free Lesson
Evaluate AI with Jev: When Classification Beats an LLM
45 min
Oct 9, 2026 12:00 PM
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What you'll learn
Tell When Jev Beats GPT-5.5 on Evaluation Cost
See why a label call costs up to 170x less than GPT-5.5, and which tasks still need a generative model.
Audit Your LLM Calls for Jev Candidates
Scan your logs for yes/no, label, and score calls, the fast wins that don't need a generative model.
Set Confidence Thresholds That Route to Humans
Use Jev's confidence scores to decide what auto-runs, escalates to a human, or goes to an LLM in 70-500ms.
Model Jev-First vs. LLM-Only Cascades Live
Walk through a live cost and latency model, then plug in your own volume to see which architecture wins.
Why this topic matters
Many teams pay for LLM calls that only return a label, yes/no, or score. TypeSafe's Jev, launched September 15, 2026, handles those calls at about 4.2 cents per million input tokens, up to 170x cheaper than GPT-5.5, in 70-500ms, with a confidence score on every answer. That makes human-review routing and agent guardrails practical. Results are vendor-reported, so this session shows PMs how to test Jev on their own data before betting the roadmap.
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