Neosigma uses Jev as an agent trace verifier
Across 10,000 verifier decisions, Jev was 6.2x cheaper and 34x faster than GPT-5 Mini, with 88% agreement with human labels.
The cost of verification sets a ceiling on how much agents can learn from production. When you can only afford to evaluate a small sample, most of that experience goes unused. Cheap, fast verification raises that ceiling: more failures discovered, more representative evals, and more feedback to improve the model and harness. At @neosigma_ai, our work with Jev makes us optimistic about a future where learning from production is a continuous part of how agents operate. Across 10,000 verifier decisions, Jev was 6.2× cheaper and 34× faster at median latency than GPT-5 Mini, with 88% versus 85% agreement with human labels in a blinded 100-trace audit. full blog here - https://neosigma.ai/blog/verifying-agent-traces-at-scale-with-jev
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