When a product needs to classify, score, or route text, the hard part is often choosing a decision model that behaves well for the job. A useful workflow is to make the question structure explicit, compare several models on the same inputs, and only then move the best candidate into an application.
Start with a structured question
A decision task is easier to evaluate when its expected output is clear. For example, a Choice question can select one label, a Score question can return a rating, and a yes-or-no question can answer a binary check. Keeping the input and output shape consistent makes model comparisons more meaningful.
Compare before you route
Decisions API is an independent workbench and API for exploring hosted decision models. Its playground supports structured Choice, Score, and Noul questions over text or JSON, so a team can compare models before sending requests to a shared API endpoint. Supported models can also accept image inputs. See the Decisions API playground to explore the workflow.
The same approach helps with routing: use a small evaluation set, record where models disagree, and keep the examples that expose edge cases. The goal is not to pick a winner once, but to make the trade-offs visible before they become production behavior.
Decisions API currently lists 13 hosted models. New accounts receive 100 credits shared across the playground, API, and evaluations; one-time credit packs start at $10 and credits do not expire. Model rates vary, so measuring a representative set of requests is still important.
A compact checklist
- Define the output shape before comparing models.
- Test the same text or JSON examples across candidates.
- Inspect disagreements and borderline scores.
- Route only after the evaluation set reflects real traffic.
This keeps model selection tied to observable behavior rather than a vague preference for a particular model.
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