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*For more information on AI Tagging at EdgeTier, visit our existing documentation*

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AI Tagging (or AutoTagging) is a large-language-model approach to automatically applying labels to all interactions in EdgeTier. AI Tagging is designed to transform how customer interactions are classified, making tagging more precise and less time-consuming. Built using a Large Language Model (LLM), this feature ensures that every interaction is assigned a tag from a predefined list. This happens automatically and consistently.

In plain terms, EdgeTier’s AI tags every interaction’s Contact Reason for you, without needing to set-up any phrase tags or triggers.

Why we built this

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This feature was initially developed to provide a structured, automated way to categorise entire interactions without the need for manual selection or complex trigger setups.

Until now, this has been implemented through collaboration with EdgeTier’s team: you define your categorisation goals, and we create specialised tagging models to help you achieve them. You could always see these tags on your interactions across EdgeTier, but you could not visualise them or their underlying rules in any dedicated page.

We’ve now added an interface to allow any EdgeTier user in your organisation to view the Contact Reason categories being applied, so it's easier to understand and trust the AI output.

This new page is a home for your Contact Reasons, and a first step to full self-service AI tagging in the interface. It allows you to view all categories and the definitions and use cases behind them.

The changelog can tell you updates made to your AI tags by the EdgeTier team, including the user and what was changed with a timestamp.