Hey, every metric you've listed is native eazyBI — active CRs, untouched issues, 90-day rolling waits, rejection-reason breakdown, MTTR end-to-end. The bit most people miss: you have to enable Import issue change history and Import comments on the data source. Without those flipped on, none of the time-in-status or activity measures work — which is probably why the marketplace apps felt limited. Letting an LLM do the calculations themselves gives you non-deterministic numbers (same prompt, different totals), no audit trail when someone asks how MTTR is defined, and a token bill that scales with your data. Where AI genuinely earns its keep is on top of eazyBI — clustering messy free-text rejection reasons into themes, generating narrative summaries, anomaly detection on a dashboard. The architecture that works: Jira → eazyBI for the numbers → AI for the story. Happy to share measure definitions if useful.