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Compare decision models on a whole workflow

Prasanth Jayachandran reports Isotopes AI’s comparison of four models on follow-up questions inside its own data-analysis app.

Original by Prasanth Jayachandran / Isotopes AIEvaluation

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Our summary

A follow-up such as changing a chart’s dates can require several connected choices. Isotopes AI tested whether its app could answer from data already in the browser or needed a larger agent team. The company compared four model versions on eighty-eight scenarios, repeating the same scenarios three times.

The app kept a confidence cutoff of 0.50 and checked whether decisions preserved the requested conditions. Jev 1.13 passed 100 percent, Jev 1.14 preview 93.6 percent, OpenAI Decisions 68.2 percent and Microsoft Decision 1 62.1 percent. Those are the app’s requirement and routing checks, not a general ranking of intelligence.

Median decision-and-composition times were about 0.81, 0.84, 1.55 and 2.71 seconds in that order. They exclude final routing, execution and later fallback work. Early failures can shorten a run, so the article also compares the same thirty-eight scenarios that succeeded for every model. The private suite covers one application.

Key takeaways

  1. Keep application rules fixed and check that every requested filter survives the model’s decisions.
  2. A confident answer can still omit a date restriction; a confidence cutoff is not a correctness test.
  3. Compare the same successful cases as well as all attempts, and separate stage timing from total user wait.

This is the app maker’s private regression suite, not 264 distinct tasks or a public benchmark. Microsoft used OpenRouter/Azure; Jev and OpenAI used direct connections. Only a subset of passing output rows was checked against fixture data.

Isotopes AI · Original published

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