A visitor asks about pricing in chat at nine at night. The widget says we'll get back to you. Nobody does until ten the next morning, and by then they've found the answer somewhere else, or not at all.
Most of those questions are answerable from what you already know: the docs, the pricing page, the past threads. The work is connecting a specific question to the specific answer, and that work is five to fifteen minutes each, forty times a week. At a small company nobody owns it, so the founder does it between building, and it doesn't scale.
Every unanswered question is a lead leaving the building quietly.
A visitor asks do you support SSO, and the AI checks the knowledge base, finds the article, and answers with a link. Replies are grounded in your content and match your voice. When a question falls outside what it knows, it says so and refuses to make something up rather than guessing.
When the same question comes in three weeks running, the AI notices the pattern and proposes an article answering it. You approve the draft, it publishes, and the next visitor gets answered directly. When your product changes, the AI flags articles whose language is now stale and proposes updates.
It can. Review catches most errors, not all. For high-stakes replies, legal, financial, or medical, you can set human-in-the-loop on every message. The AI refuses out-of-context questions rather than guessing, which is where most wrong answers come from.
No. No SLA management, no multi-agent queues, no complex ticket routing. For a high-volume support operation, Zendesk or Intercom Fin is the category. This handles the questions genuinely answerable from what you know.
Enough that your inbox holds a few real threads instead of forty. Resolution rates are ordinary for AI chat, not a headline number, and we won't quote a specific figure in early alpha. You'll see the real rate on your own traffic.
Sync your knowledge base and put the AI on your chat. It answers what it can and hands you the rest, with the transcript.