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Workflows

Use AI to classify topics and intent

Add semantic decisions when exact text matching is too brittle.

CCorthex product guidesUpdated October 15, 20262 min read
Where to find itWorkflow builder → AI/topic condition

Before you begin

Open Workflows in the workspace navigation. Decide which event should start the flow and which agents should receive it. Start with an unpublished draft.

Example workspace · Demo data. 1 — Conditions decide whether the action path is eligible. Select the image to enlarge it.
Workflow branch inspector with page condition and all/any match controls

Example workspace · Demo data. 1 — Conditions decide whether the action path is eligible. Select the image to enlarge it.

Step by step

  1. 1

    Define the category

    Describe the intended subject and exclusions. “Installation support” is clearer when you explain whether product sizing or order tracking belongs elsewhere.

  2. 2

    Provide representative context

    Use the message/conversation fields the condition supports. Avoid sending unnecessary personal data to a decision provider.

  3. 3

    Choose the supported decision settings

    Use the offered AI/provider options. Jev-backed decisions require the workspace’s relevant privacy approval and server-side configuration; availability is not implied by selecting a label.

  4. 4

    Test ambiguity

    Try paraphrases, mixed topics, short messages and an unrelated topic. Inspect the trace and fallback behavior rather than trusting one positive example.

Good to know

AI classification is probabilistic. Keep important eligibility and identity checks deterministic. Available fallback LLM decisions can consume model usage.

A topic match should route help, not silently authorise refunds, account access or policy exceptions.

Check the result

Test matching, non-matching and missing-data cases. Review the publication, publish the steps and save the intended agent assignments.

Questions & troubleshooting

A category is selected too often

Narrow its definition, add exclusions and test nearby categories. Use deterministic conditions around the AI decision when possible.

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