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Glossary

Intent Classification

Intent classification is the step that determines what an inbound request is actually asking for, mapping unstructured text to a defined category of work. Accurate classification routes each WorkItem to the right workflow, evidence sources, and policy, making it the foundation of reliable automation.

Synonyms: intent detection, request classification, intent recognition, routing classification

Intent classification answers the first question any automation must resolve: what kind of work is this? By mapping a messy request to a defined intent, the system selects the appropriate extraction fields, evidence sources, and approval policy. Because every later step inherits this decision, classification quality is measured rigorously with evaluation gates and monitored for drift. When confidence is low, a well-designed system routes the ambiguous case to a person rather than guessing, keeping accountability intact at the very start of the workflow.

Frequently asked questions

Why is intent classification important?
It decides the entire downstream path. A misclassified request retrieves the wrong evidence and applies the wrong policy, so classification accuracy gates the quality of everything that follows.
How is classification accuracy measured?
Through evaluation gates over a labeled set, tracking precision and recall per intent and watching for confusion between similar categories before a workflow goes live.