Stop staring at dashboards. Just ask.

Paste a customer message. The agent pulls their session, finds the error they hit, walks their funnel, and tells you what to reply.

Distinct users who hit a crash divided by DAU, per app version. The industry-standard mobile health metric — surface version-by-version drops fast.

Diff error fingerprints before and after the latest deploy SHA. Surface regressions in 30 seconds, including a candidate fix.

Multiply users-affected by their plan ARR to surface the bugs costing real money. Stop triaging by event volume.

Rank API endpoints by p95 latency, error rate, customer, and plan so engineering can fix performance where it affects revenue.

Compare page-load and interaction timing by release, browser, and route so frontend regressions are visible beside errors.

Show where customers fail while connecting integrations so engineering and CS can fix the highest-impact setup blockers.

See which background jobs are backing up, retrying, or landing in dead-letter queues before customers notice stale state.

Background sync, refresh, prefetch jobs fail silently and degrade UX. Group failures by task_name and network_type to find the patterns.

Split client-side errors by browser and version. Surface fingerprints concentrated in one engine — usually older Safari or a stale Chromium.

Discover which first-24h action correlates highest with day-30 retention. Most teams can't answer this. You'll answer it in 90 seconds.

Build the product-view to purchase funnel with drop-off and time-on-step. The 1-prompt ecommerce funnel that Shopify analytics doesn't ship.

Build a behavioral early-warning system that flags at-risk users while there's still time to save them. No ML team required.

Joined funnel from push provider's send webhook through open through in-app action. Per-campaign breakdown — what marketing platforms refuse to show you.

One prompt builds the full funnel from landing → activation, publishes it as a public dashboard, and ranks drop-off steps by severity.

Build the trial-to-paid funnel split by acquisition source. Surface the channel that converts 8x better than the rest.

Tie acquisition campaigns to paid conversion, revenue, and retention so marketing and finance can see which campaigns pay back.

Break down checkout completion, failures, and latency by payment method so growth teams know which option hurts revenue.

Capture failed docs searches and connect them to activation, support load, and API adoption so docs work targets real blockers.

Measure failed-payment recovery from invoice failure through retry, card update, recovery, or cancellation for subscription revenue.

Score every B2B account on usage, revenue, and support load. Publish one URL your CS team checks instead of wrangling data each QBR.

Routine runs at 2am, picks the top silent bug, investigates it, opens a draft PR if the fix is small and contained. Lights-out triage for the next morning's review.

Routine that reads the audit log every Friday and Slacks a category breakdown: cases resolved, flags toggled, surveys created. Don't trust — verify in 60s.

Create a weekly account digest for each CSM with risks, expansion signals, product adoption, and customers needing outreach.

Follow an enterprise account from kickoff through integration, first data, first value, and blocked steps so solutions teams can unblock launches.

Summarize a deploy with new errors, affected users, key metric deltas, and the next engineering action in one chat response.

Combine usage decline, errors, seat utilization, and support friction into a renewal-risk brief CS can act on before the renewal date.

Find which production errors cannot be unmangled because sourcemaps are missing, stale, or uploaded under the wrong release.

Find suppressions that are hiding high-volume, high-impact, or recently regressed errors before noise rules mask real incidents.

Combine errors, complaints, affected users, and plan data to show which accounts are consuming the most support attention.