# How Jev and Laya help support agents prepare context

Both models tried on an agent’s context step.

Grade: X — Not a typed-decision job: needs written output, plain rules or lookups would do it, or needs raw image or audio. Also marks ideas that must not be built.. Score: 2.21.

Vertical: Cross-industry.

Function: Support & CX.

Status: Seen in the wild.

Volume: occasional.

Value: meaningful.

Risk: low.

Evidence: built and shown.

Flags: None.

- [Source](https://madewithjev.com/builds/jev-laya-support-context)
- [Vertical](/verticals/cross_industry/)
- [Function](/functions/support_cx/)
- [Sentiment-based alert system](/use-cases/sentiment-based-alert-system/)
- [Churn risk prediction](/use-cases/churn-risk-prediction/)
- [Client sentiment risk](/use-cases/client-sentiment-risk/)
- [Detect PII or secrets pasted into support tickets](/use-cases/detect-pii-or-secrets-pasted-into-support-tickets/)
- [Is this agent draft reply safe to send](/use-cases/is-this-agent-draft-reply-safe-to-send/)
- [Customer satisfaction measurement](/use-cases/customer-satisfaction-measurement/)