Support ticket triage
Ask Jev to choose a queue, score severity, and estimate whether the issue needs escalation. Keep the final route and service-level policy in application code. Tickets with low confidence or regulated content should be reviewed under the team's policy.
AI model routing
Classify request complexity or required capabilities before selecting an inexpensive, balanced, or high-capability model. Evaluate routing quality and total task success together; a fast route is not useful if it sends work to a model that cannot complete it.
Agent tool-call risk checks
Score an action and ask whether it is destructive or outside policy. Use this as one signal around an agent. Enforce access with deterministic controls, scoped credentials, confirmation rules, and sandboxing rather than trusting a model score as the security boundary.
Content moderation
Use typed questions to identify policy category, severity, and whether a post should be escalated. Moderation requires clear policy definitions, appeals, human review and monitoring for false positives across different user groups.
Lead and email prioritization
Classify inbound intent, score fit against a defined rubric, and flag messages that need a human response. Avoid treating model output as a final employment, credit, or other high-impact eligibility decision.
Inspect static examples
The homepage decision lab contains four static fixtures: support triage, model routing, an agent action gate, and content review. They illustrate request and response shapes only; no live model call runs on this site.