Stop re-solving the same complaint every week
Automated customer-service root cause analysis: recurring contacts are grouped into a governed root-cause file with the evidence, the owning process and the corrective action.
The problem
- Support closes tickets one at a time while the underlying process defect keeps generating new ones.
- Nobody owns the pattern: the agent sees one case, the team leader sees a queue, and the process owner never receives the evidence.
- Post-incident reviews are written from memory days later, with no traceable link back to the conversations that triggered them.
How Quantara Flow AI does it
Recurring contacts grouped, not counted
Cases, wrap-up reasons, knowledge gaps and sentiment are analysed together so repeated contacts about the same defect are grouped into one root-cause file.
Evidence attached to the cause
Each root-cause file links the contributing cases and the knowledge gaps behind them, so the process owner reads evidence rather than an opinion.
Owner, action and status
A file carries an owner, a corrective action and a lifecycle, so it closes when the cause is fixed — not when the last ticket is closed.
Triggered automatically or opened by hand
Configured rules can open a report when a pattern crosses a threshold, and a supervisor can always open one manually.
Knowledge gaps closed at the source
Where the cause is a missing or wrong answer, the gap is recorded against your knowledge base so the correction is published once and reused everywhere.
What your operation gains
- Repeat contacts traced to a named cause with an owner
- Process defects visible to the team that can actually fix them
- A written, evidence-linked record of what was found and what was changed
- Knowledge corrections that remove the reason for the contact
What you can measure
Measured in your own workspace. We publish no benchmark figures we cannot evidence.
- Repeat-contact rate and first-contact resolution
- Number of open root-cause files by owning process and by status
- Time from pattern detection to corrective action
- Contact volume attributed to each identified cause, before and after the fix
- Knowledge gaps opened and closed
Governance and data handling
- Root-cause files are workspace-scoped and access-controlled by role.
- Every AI-generated analysis is labelled as such and remains editable by an accountable human owner.
- Contributing cases stay linked, so any conclusion can be re-checked against the original conversations.
Questions
Is this just tagging?
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No. Tags describe a single contact. A root-cause file groups contacts around one defect and carries an owner, corrective action and status until the cause is closed.
Who can open and close a file?
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Access follows your workspace roles. Analysis can be triggered automatically or opened manually, but closure is a human decision.