Exabloom watches the questions customers actually ask, spots the ones your Knowledge Hub can’t answer yet, and drafts a ready-to-approve FAQ from how your team already replied. You review the good ones and add them in a click.
Customers reveal your content gaps every day — they ask the same uncovered question over and over. But that signal is buried in conversation history and never makes it back into your FAQs.
Every customer question is checked against your FAQs and documents. When nothing answers it well, that's a logged content gap — no configuration required.
“PH hours?”, “open on the holiday?” and “u all open monday” collapse into one suggestion — and only surface once enough different customers have asked.
For each recurring gap, Exabloom drafts a clean FAQ — mining the answer from how your reps actually replied. You review it and add it in a click.
It runs quietly in the background — a nightly sweep across all your workspaces. You just see the suggestions worth reviewing.
The suggestions do the noticing and the first draft. You stay in control of every word that reaches a real customer.
The answer comes from how your team already responded to that question in chat. If no one ever answered it, the draft is left blank and flagged — so you fill a real gap, not a guess.
Every suggestion is a draft. Accept opens the normal FAQ editor, pre-filled with the question, the answer, and a suggested folder. Nothing enters your Knowledge Hub until you save it.
Each suggestion shows how many customers asked, across how many workspaces, plus real (read-only) message snippets — each one a click away from the actual conversation.
Dismiss a suggestion and its topic stops cluttering the queue — but it keeps counting quietly, and resurfaces if it becomes a bigger problem. A Dismissed view lets you bring any back.
A question becomes a suggestion only after several different customers ask it — one-offs never create noise. And because a suggestion exists only when your Hub has no good match, accepting one fills a real hole rather than restating an FAQ you already have.
The same handful of questions is most of your inbox. Learned Q&As turns the top repeats into FAQs your AI can answer on its own — so your team stops retyping.
Suggestions are brand-wide but read every workspace's chats, each attributed to where it came from — so the same gap at Tampines and Bukit Timah becomes one FAQ, not two.
Set it up once, then never notice it drifting out of date. The gaps surface themselves as your customers' questions change — so your FAQs keep pace without a content project.
You'll never read every conversation to find the patterns. This does the reading for you — and hands you a drafted answer to approve, not another to-do.
What teams want to know before letting the AI draft their FAQs.
It's in active development right now. We're onboarding early-access partners — small group, lots of attention. If you want to be one of them, message us on WhatsApp and we'll add you to the rollout list.
Still have a question?
Ask us on WhatsApp →Early-access partners are getting onboarded now. Small group, hands-on rollout. If your FAQs never quite keep pace with what customers actually ask — this closes the gap for you.
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