Use cases· Last updated

Support triage with Jev

Customer support is the example TypeSafe uses throughout its docs: incoming tickets need a queue, a temperature reading, and time pressure — a Choice, a Score, and a Noul on one state. This hub is the full pack (not a single recipe). Unofficial. Official bodies: quick start. We do not issue keys.

Pack (read in order)

  1. Decision workflow — contracts, question map, cascade abort
  2. Confidence thresholds — risk-scaled floors
  3. Human handoff — what reviewers see
  4. This page — official ticket sketch + use-case map extras
  5. Intent routing — when some intents skip LLMs

Official three-question ticket

Use TypeSafe’s quick-start body (department / frustration / is_urgent). Put ticket text, product, and policy excerpts in structured state. Point at ticket.body.

Then code:

  1. Choice confidence below your floor → handoff
  2. Else route on department.choice (include other)
  3. High is_urgent.noul jumps the queue; band near 0.5 gets a second look
  4. High frustration and technical → page only if your conjunction says so

What the use-case map adds

TypeSafe also lists: extract issues and commitments from call transcripts; detect churn risk and refund requests; verify drafted replies against policy. Each is more questions on the same or a follow-up state — not a different product. Reply text still comes from a template or LLM.

Deep taxonomies: cascade Choices with confidence abort (workflow), following their hierarchical cookbook — we do not clone a rival recipe page.

FAQ

Can Jev replace the agent? No. It classifies and scores. Agents (or humans) act.

Do we publish triage accuracy? No. Run offline evaluation.

Hub: Use cases. Official: docs.typesafe.ai.

Sources

Public TypeSafe or adjacent documentation only. No private claims.