Tag
12 posts with this tag.
Most B2B SaaS teams have SLAs for ticket response and PR merge, but no one measures the hours a bug spends in limbo between Zendesk triage and a structured engineering receipt, and that unmeasured gap is where churn hides.
Watari extracts a structured bug from a Zendesk or Intercom ticket, maps it to a specific file and function in Azure Repos via Microsoft Entra ID, and opens a draft pull request, without manual copy-paste between your support queue and Azure DevOps work items.
Bugs don't stall because teams are careless. They stall at a specific structural moment when support has triaged a ticket but the artifact crossing to engineering is too incomplete to act on.
Watari connects to Freshdesk via API key, extracts severity, repro steps, and expected-vs-actual behavior from free-form tickets, and opens a reviewed draft PR on GitHub, without any manual rewrite between support and engineering.
Before building Watari, we held three confident assumptions about why the support-to-engineering handoff breaks (volume, routing, and fix speed) and all three turned out to be wrong in ways that reshaped every pipeline stage we built.
Most Zendesk and Intercom tickets land in Linear as half-filled issues with no repro steps and wrong severity. This post shows how structured extraction and duplicate detection fix that before the sync ever fires.
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.
This post shows support and engineering teams how to replace the manual rewrite tax (the 15–30 minutes spent reformatting a Zendesk or Intercom ticket into something actionable) with structured extraction, CODEOWNERS-aware routing, and a closed feedback loop.
Most teams fix the bug but never tell affected customers what happened. That silent close is a churn trigger. This post explains how to write and deliver a structured, jargon-free root cause analysis that converts a support cost into a retention signal.
The support-to-engineering handoff breaks at the format boundary, free-form Zendesk and Intercom tickets are structurally incompatible with what engineers need, and no amount of Slack messages or Jira fields fixes a format mismatch.