Occupation Classification API Use Case

Problem

Organizations often receive job titles and descriptions that are inconsistent, incomplete, or difficult to map to standardized occupational structures.

How AvelinLabs Helps

AvelinLabs helps classify job text into O*NET 30.3-grounded occupation outputs. The API is designed to return structured results that applications can evaluate, display, compare, or route for review.

The production POST /api/v1/occupation/candidates endpoint is a separate candidate-shortlist tool. It can retain multiple plausible occupations for ambiguous or compound roles, always returns mapping_selected=false, and does not make or persist an official mapping. Use /job/analyze or /job/classify only according to their existing contracts; the shortlist does not change their behavior.

Why It Is Different

The result is more than a generated occupation label. It is a structured decision with standard occupation identity, supporting signals, confidence, uncertainty, and review context where available.

Input Signals

Useful inputs may include:

• job title
• job description
• skill-bearing text
• location or market context where supported

Decision Output

Occupation classification outputs may include:

• ranked occupation results
• O*NET codes and occupation metadata
• confidence, trust, uncertainty, and ambiguity signals
• skill evidence
• explanation and quality fields
• related occupation context

Product Fit

This use case can support analyst tools, workforce intelligence products, labor-market dashboards, career-pathing workflows, and applications that need standardized occupation context from unstructured job text.

GitHub Example Reference

Complete executable examples live in the official AvelinLabs API examples repository. For shortlist behavior, start with the occupation candidate payload and serializer-produced response.