Watari

Customer bugs, located in your code. Watari reads each Zendesk ticket you send it, including screenshots, screen recordings, PDFs, voice notes and logs, and turns it into a structured bug report: severity, steps to reproduce, impact, and the customer's own words. It then ranks the files and functions in your repository most likely to contain the defect, with the reasoning for each.

A draft fix your engineers review. When it is confident enough, Watari opens a draft pull request on GitHub (or a pull request on Azure DevOps). Your reviewers and your own CI decide what ships. Watari never merges.

Duplicate reports collapse into one bug. When five customers report the same regression, your engineers see one issue, filed in Jira, Linear, GitHub Issues or Azure Boards, with every ticket linked to it.

Customers hear back when the fix is live. Watari drafts a plain-language root-cause update. After someone on your team approves it and the deploy is confirmed, it is posted to every Zendesk ticket that reported the bug, as a public reply or an internal note (your choice per update). Updates can be translated into each customer's language.

How it works with Zendesk
- You choose one or more Zendesk tags. Watari creates a webhook and a trigger in your account that forward tickets carrying any of those tags. Untagged tickets are never sent.
- The only thing Watari writes to a ticket is the root-cause update your team approved. It does not change ticket status, tags or assignees.
- Disconnecting removes the webhook and trigger it created.

Also works with Intercom and Freshdesk for support, GitHub and Azure DevOps for code, Slack and Microsoft Teams for alerts.

Pricing. You pay per Mapped Issue: a ticket Watari turns into a bug or feature request and maps to your code with high confidence. Draft pull requests, root-cause updates and issue-tracker sync are included. The 14-day trial includes 10 Mapped Issues and needs no card. Plans at https://watari.ai/pricing.

Your data. Integration tokens are encrypted with AES-256-GCM, each workspace is isolated with row-level security, and your data never trains models. Our mapping accuracy, misses included, is public at https://watari.ai/proof.

Data Watari accesses, and why
- Reads: only tickets carrying your chosen tags: subject, description, public and internal comments, status, tags, attachments, names and emails of the requester, submitter and assignee, and the requester's organization name.
- Why: to write the bug report, find the related code, group duplicates, and address the update to the right people.
- Writes: only the update your team approves, as a comment on the reporting tickets.
- Stores: in your Watari workspace (AWS us-east-1). Processed by the subprocessors at https://watari.ai/legal/subprocessors. Deleting your workspace deletes it after a 30-day grace period. Details: https://watari.ai/legal/privacy