Find what you didn't know to look for.
Auto-categorization reads all your interactions and discovers categories for you — no training, no labels, no instructions. It finds the patterns you didn't know existed.
Point it at your data. Get categories back.
The AI reads every conversation, finds recurring patterns, names them, ranks them by volume and cost, and flags what's new. No setup required.
Auto-discover and custom-train. Together.
Auto-categorization finds what's happening. Custom models classify it your way. The two work side by side — the AI discovers patterns you didn't expect, and your trained models enforce the structure you need.
AI reads everything and groups it. No instructions, no labels. Finds what you didn't know to look for. Best for exploration, discovery, and finding blind spots.
You define the categories. Train with examples. Get production-grade accuracy. Best for KPIs, dashboards, playbooks, and anything that needs to be precise.
The things you didn't know were costing you money.
Auto-categorization doesn't confirm what you already know. It finds what nobody noticed — because no one was looking for it.
"Router won't connect after restart" is 12% of tech support — but it was buried inside "broadband issues" in your old categories.
Summer house internet setup calls spike 340% in May. Visible only when the AI separates it from general "new service" requests.
"App crashes on firmware v3.2" — the AI found it in 1,200 calls. Your old keyword search missed it because customers said "freezes", "stops working", "black screen".
The AI discovered a cluster of 1,400 calls mentioning a competitor's new pricing — before marketing knew about the campaign.
2,100 calls about "wrong amount on invoice" — but 60% are actually about VAT changes, not billing errors. Completely different fix needed.
"Just checking my contract end date" — seems innocent, but the AI found these customers churn at 4x the normal rate within 30 days.
Found something interesting? Make it permanent.
When auto-categorization discovers a pattern worth tracking, you can turn it into a custom model with one click. The auto-discovered examples become your initial training data.
Discovery feeds everything.
Auto-categorization is the first step. What it finds flows into Custom Model Training for precision, Dashboards for monitoring, and Contact Reasons for the full breakdown.
You can't fix what you don't know exists.
Auto-categorization eliminates blind spots. It reads everything and tells you what's really happening — without assumptions, without bias, without missing anything.
Categories auto-discovered
Labels required
Average integration window
