JEV / USE CASES

Find a decision worth automating.

Start with a runnable example. Change the state and the questions in the workbench, then inspect the typed result before you use it in code.

Evaluation & matching

Check answers against evidence and compare records.

Answer quality

Check an AI answer against evidence and a quality rubric.

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Entity matching

Spot likely duplicate records for human review.

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Retrieval & context

Rank evidence and decide what context to retain.

RAG relevance

Rate whether retrieved text answers the user’s question.

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Context selection

Decide which note deserves scarce context space.

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Agents & routing

Choose the next action, model or approval path.

Agent routing

Pick the next safe step for an assistant.

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Agent action gate

Test the approval path before an external tool action.

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Model routing

Choose a fast or deep path for an incoming request.

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Support

Route customer requests and identify knowledge gaps.

Support routing

Assign a customer message to a queue.

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Knowledge-base gap

Check if a retrieved excerpt can support a reply.

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Trust & safety

Review content and check claims against evidence.

Content review

Estimate whether a post needs a human check.

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Evidence check

Judge whether context supports a claim.

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Growth

Prioritize leads and understand customer feedback.

Lead scoring

Prioritize a sales follow-up.

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Feedback intelligence

Classify feedback and rate follow-up priority.

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Operations

Triage incidents and assess release readiness.

Incident triage

Get an owner, urgency score, and escalation signal from one alert.

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Release readiness

Score a rollout and flag unresolved safeguards.

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