As AI systems move from demos into real workflows, the difficult part is often not generating text. It is deciding what should happen next. A support request may need a category, a score, a route, or a safety check before it reaches a person or another agent. That is the problem space DecisionsApi is designed to explore.
DecisionsApi is a developer-focused AI platform with an online playground and an API. Developers can provide text, JSON objects, or arrays of text as state, then define typed Choice, Score, or Noul (yes/no) questions. The service returns structured answers with probabilities, confidence, usage, and request details. The result is intended to be easier to pass into application logic than an unstructured paragraph.
A useful workflow starts with a small decision model. A team can ask a Choice question to classify an incoming request, use a Score question to estimate a value, or use a Noul question for a yes/no gate. Those outputs can support customer-request routing, agent next-step selection, evidence checks, safety gates, and human-review workflows. Because the playground and API share one credit balance, a developer can test a model interactively and then connect the same idea to an integration.
The product also includes API key management and usage history. This matters when a team is comparing models or building an internal workflow that needs to understand how requests are being used. Instead of treating model output as the final answer, a structured decision can become one step in a larger system: classify, route, check, and escalate when necessary.
For developers who want to examine this approach, the project is available at DecisionsApi. Its tagline is “Text in. Decisions out.” This approach is useful when a team wants to keep model experimentation visible while making the final output predictable enough for downstream software. It also makes it easier to separate a model judgment from the application logic that decides whether to continue, route, or request human review.
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