Use case
AI support for discovery calls
The follow-up question you'd have thought of afterwards.
The short answer
Discovery calls fail when the seller accepts a surface answer. Axelize listens to the buyer's response live, identifies which qualification dimension is still unresolved, and suggests the specific follow-up question that surfaces it, while asking it is still natural.
The moment
The buyer gives you an answer that sounds complete but isn't. The qualifying question sits one layer underneath it, and by the time you notice, the conversation has moved on.
What that looks like
On a discovery call, Nestor Wilke from Northwind Traders says: “We're mostly just exploring options at this point.” Axelize finds: Northwind announced a new wholesale channel in its third-quarter update, with a team being hired to sell into it. It suggests: “Makes sense. You announced the wholesale channel last quarter, so is this about the team you're hiring to sell into it, or something else that changed?” Treats 'just exploring' as an answer with a cause behind it, and asks about the cause the account research already points to.
What Axelize does
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Gaps are tracked
Budget, authority, need and timing are tracked across the call, so you can see what has genuinely been answered.
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The next question is proposed
Phrased as a question you'd actually ask out loud, not a checklist item.
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Answers land in the record
What you learn attaches to the account, so the next call starts from it.
Frequently asked questions
- Does it follow a specific methodology?
- It tracks need, authority, budget and timing, the same dimensions MEDDIC and BANT cover, without forcing you to run the call as a checklist.