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8 posts with this tag.
Watari eliminates the manual copy-paste tax between Zendesk and Jira by extracting severity, repro steps, and customer impact automatically, then syncing a well-formed Jira issue only after both confidence gates clear.
Most B2B SaaS teams have a tight fix loop from Zendesk ticket to GitHub PR, but a completely broken notification loop — and that silence after the fix is the actual churn trigger, not the bug itself.
Manual escalation routing fails in two predictable ways — wrong team, wrong queue, days of silence. This guide explains how code-location mapping and CODEOWNERS-driven assignment eliminate both failure modes.
Most support teams assign severity by gut feel or customer loudness — this post explains why structured extraction, confidence gating, and code-location matching are the only reliable way to protect engineering triage time.
A support ticket and a bug report are structurally incompatible artifacts — one is written for human empathy, the other for engineering reproduction — and that format mismatch is the real cost hiding in your support-to-engineering handoff.
Intercom conversations lack a subject line, mix bot noise with real repro steps, and fragment context across dozens of short messages — this post explains how structured bug extraction handles the chat format and routes actionable reports to GitHub, Linear, and Jira.
A customer-facing RCA that names what broke, what fixed it, and what prevents recurrence turns an incident into trust — this guide shows exactly what to include and what to leave out.
This post walks through how Watari automates the lossy, manual path from a Zendesk support ticket to an engineering-ready bug report — including OAuth setup, structured extraction, noise filtering, code mapping, and draft PR generation.