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PythonGradioMLflow

Support Ticket Triage Platform

A support-ticket triage platform with a Gradio UI and MLflow experiment tracking for model iteration.

Illustration for the support ticket triage platform project, showing a Gradio interface predicting ticket category and priority

Problem

Support teams waste time manually routing and prioritizing incoming tickets before an agent can even start solving the problem.

Solution

A triage classifier with a Gradio UI for real-time predictions and MLflow tracking, so model versions can be iterated on with confidence.

Overview

Every minute a support ticket sits unrouted is a minute an agent isn’t solving it. Manual triage is one of the most avoidable delays in a support workflow.

How it works

A triage classifier predicts ticket category and priority the moment a ticket arrives, exposed through a Gradio UI for real-time testing and demoing. Model iterations are tracked in MLflow, so a new model version can be compared against the previous one before it’s trusted with real tickets.

Result

Tickets get routed automatically instead of sitting in a queue waiting for a human to read and categorize them first.

Further reading

See From Notebook to Data Product for more on why version tracking and a usable UI matter here.

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