Replacing manual triage with an applied AI workflow
An operations team was drowning in repetitive classification work and existing tools didn't fit.
Problem
An operations team spent hours each day manually classifying and routing incoming requests. They'd tried existing automation tools, but none fit their specific workflow — they were either too rigid or required a complete process overhaul. The team needed AI that supported their judgment rather than replacing it.
Approach
Qnaku designed and built a focused AI copilot wired directly into the team's existing tooling — not a standalone chatbot. The system used a retrieval-augmented pipeline to suggest classifications, which the team could approve, edit, or reject. This kept human judgment in the loop while eliminating the repetitive work.
Outcome
Manual triage time was reduced meaningfully, and the workflow stayed inside the tools the team already used. No process overhaul required. Placeholder — specific metrics available on request.
Note: This case study uses illustrative content. Specific client names, metrics, and outcomes are withheld by agreement and available on request.
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