OpenAI makes the Decisions API generally available for bounded choices

The developer guide distinguishes predicates, choices and scores. A predicate estimates whether a condition holds; a choice selects from provided options; a score evaluates ordered levels. These are bounded results, rather than a general request to generate a document or an arbitrary structured object. The distinction is useful when the application already knows its possible next steps.

The guide is explicit that the application performs any action selected by an answer. A classification endpoint does not authorize a refund, grant access or execute a deployment. This separation is easy to lose when a result is wired directly into a workflow. Keep the policy that permits an action distinct from the model output that proposes it.

Before integration, define a small set of decisions and assemble representative examples, including ambiguous and adversarial inputs. Decide what should happen when evidence is incomplete or several categories are plausible. An escalation path can be more useful than forcing a confident-looking selection. Keep deterministic checks around identifiers, account ownership and monetary limits; a model should not be the only control between an incoming message and an irreversible operation.

Application teams building routing, triage or validation workflows can evaluate whether a bounded result is sufficient. A useful pilot might classify incoming work while a person still makes the final operational decision. Observe disagreements, retries and processing cost with consent-appropriate data. Production request limits, data handling and regional availability must be verified against the account's current documentation and configuration.

General availability does not prove accuracy for a particular domain, eliminate prompt injection or establish that a probability is calibrated for local policy. No latency or cost saving has been independently benchmarked by absequ for this report. Our interpretation is that a smaller output contract can simplify application design, provided teams retain explicit authorization, measured evaluation and a safe response to uncertain evidence.