AI Chatbot for SaaS Support: Answer Product Questions From Your Docs
Your docs, help center and pricing pages already hold most of the answers your SaaS users and prospects ask for. The trouble is that people would rather ask than search. An AI chatbot for SaaS support answers from those pages, shows the source for every sentence and brings in your team when a person should step in. Here is how to set one up.
Step 1: Point it at your docs and help center
Add your website and docs as a source, and limit reading to paths like /docs/** or /help/** if you only want those. For content that is not public, add PDF or Markdown files, or connect Google Drive. Every answer cites the pages it used, so users can open the article and your team can see which page to fix. Public pages only: anything behind a login cannot be read.
Step 2: Put the chat where users already look
A corner bubble works on marketing pages, but readers in your docs often prefer something else. The same agent can open as a search palette opened from a button, as a sidebar next to your docs, or as a full help page. Pick one of the chat templates, add your logo and greeting, and publish when it is ready. Installing it takes one script tag just above the closing body tag (or in your builder's footer code), and you can add your app's domain to the allowed domains to run the chat inside your app.
Step 3: Let it say "I don't know"
The worst thing a support agent can do is make something up. The agent is told never to state a feature, limit or price that your content does not state. If your docs do not cover a question, it says so and offers the next step you chose: a contact form, an apology, or a person from your team. Questions it could not answer are grouped by meaning, so you see which article to write next. Answer a group once with a saved answer, and the next user gets that answer.
Step 4: Decide when a person steps in
Handoff needs a paid plan. With handoff turned on, when a user asks for a person, or, by default, when the agent cannot answer twice in a row (the first time it offers a button), the chat goes to your team with a short summary: what the user wants, what was tried, their intent and mood. Your team takes over in the inbox, in Slack or in Discord, and the user stays in the same chat.
Step 5: Test it on real questions before launch
Export past tickets from your helpdesk as a CSV and run a ticket replay. The agent answers your real customers' questions and shows how many it covers, how many it would send to a person, and which gaps to fill. Tests written from your own content score the agent too, with a one-click way to fix each miss.
Step 6: Keep it current
Your docs change with every release. Sources are read again on a schedule set by your plan, and you can press Sync now on a source to read it at once. Saved answers are live the moment you save them.
Try it on your own docs
See how OneType answers from your documentation before you put it in front of users: AI chat for SaaS.