Add a chatbot to your help desk, documentation site, or knowledge base. Users ask questions in plain language and get answers instantly. No more digging through articles, scrolling through categories, or guessing which search terms will work.
If the first few keyword searches don't return the right article, most users stop trying. The answer is in your docs, but the search experience fails them.
Your documentation is organized by your internal structure, not by the questions your users actually ask. They end up clicking through categories that don't match their mental model.
Sometimes the answer isn't in one page. It requires reading three articles and connecting the dots. Most users won't do that. They'll contact support or give up entirely.
Developers land on your docs looking for a specific endpoint, parameter, or code example. Traditional documentation makes them hunt through pages when they just want a direct answer.
Ingests content from your help desk, documentation site, wiki, API reference, PDF manuals, and more. All of it becomes searchable through a single conversational interface.
Users ask questions in their own words. The chatbot understands the intent and returns the answer directly, pulling from the right article or section. No keyword guessing.
Every answer includes a link to the original article or documentation page. Users can verify the source and read deeper when they want to. No black-box answers.
For API documentation and technical content, the chatbot returns code examples, endpoint details, and parameter descriptions formatted correctly. Developers get answers they can copy and use.
See exactly what users are asking that your documentation doesn't cover yet. Every unanswered question becomes a signal for what to write next.
When your documentation changes, the chatbot's knowledge updates automatically. No manual retraining, no stale answers. Publish an article and the chatbot knows about it.
Developers ask "how do I authenticate with OAuth2?" or "show me the request body for creating a user" and get the answer with code examples, right from your API reference.
Users ask "how do I reset to factory settings?" or "what's the maximum weight capacity?" and get a direct answer pulled from your product documentation, with a link to the full page.
Customers describe their problem in their own words. The chatbot finds the right help article and gives them the answer directly. No category trees, no keyword guessing.
Whether it's a public-facing knowledge base or an internal wiki, users can ask questions and get answers that pull from across your entire content library. No more "which article was that in?"
Most users don't want to talk to a bot. They want a fast answer. But searching a help center, scrolling through FAQ pages, or clicking through knowledge base categories rarely gets them there.
ChatBotHouse sits on top of your existing content. Users ask a question in plain language and get the answer straight from your help articles, FAQ, or docs. If they need more help, you can optionally give them a way to reach your support team directly.
How do I change my billing email?
Go to Account Settings → Billing → Contact Info and update the email address there. Changes take effect on your next invoice.
Source: Managing Your Billing Settings
Can I add a second billing contact?
Yes. On the same page, click "Add billing contact" to include additional email addresses. Each contact will receive a copy of invoices and payment receipts.
Source: Managing Your Billing Settings
The chatbot supports 40+ languages natively. Even if your documentation is only in English, users can ask questions in their own language and get answers back in that same language. No separate bots, no translation layers.
¿Cómo configuro la autenticación de dos factores?
Ve a Configuración → Seguridad → Autenticación de dos factores. Puedes usar una app de autenticación o SMS.
Fuente: Configuración de seguridad
Source article: "Security Settings" (English) → responded in Spanish
Web pages, help desk articles, API documentation (OpenAPI/Swagger), Markdown files, PDFs, Word documents, and most structured content formats. If your content is published somewhere, the chatbot can likely read it.
The chatbot's knowledge base syncs with your content sources automatically. When you publish, update, or remove an article, the chatbot reflects those changes without manual intervention.
It says so honestly rather than guessing. The question is logged so you can see what's missing from your documentation. If you want, we can also set it up to offer users a way to contact your support team. Checks are in place to reduce inaccurate responses, though no AI system can guarantee perfection.
Yes. The chatbot understands API reference structures, endpoint details, parameters, and code examples. It returns code formatted correctly so developers can copy and use it. It also supports follow-up questions like "show me the same request in Python."
Yes, significantly. Most support tickets from documentation users exist because those users couldn't find the answer, not because the answer doesn't exist. A chatbot that understands natural language and pulls answers from across your entire docs library solves that gap. Users get instant answers to questions like "how do I configure SSO?" instead of opening a ticket and waiting. The unanswered questions get logged, so you also learn what's missing from your docs and can fill the gaps.
A lightweight chat widget that we match to your brand: colors, logo, and positioning. It loads asynchronously and doesn't impact page performance. We can also embed it directly into your documentation layout if you prefer a non-widget approach.
Knowledge base implementations are one of our fastest builds. 1-2 weeks for discovery and content ingestion, 3-5 weeks for proof of concept. Most clients are live within 6-8 weeks. You'll see a working demo on your actual content within two weeks of starting.
Yes, and this is one of the biggest advantages over traditional search. When a user asks a question whose answer spans three different articles, a search engine returns three separate results and leaves the user to connect the dots. The chatbot synthesizes information from across your entire documentation library and delivers a single, coherent answer with links to each source. For complex questions like "how do I set up SSO with SAML and then configure role-based permissions?" the chatbot pulls from both the SSO article and the permissions article in one response.
For the way most people actually look for help, yes. Keyword search requires users to guess the right terms. A chatbot understands intent. Someone who types "it's not letting me log in" gets the same answer as someone who searches "authentication error 403." The chatbot also handles follow-up questions in context, so a user can say "that didn't work, what else can I try?" without starting over. That said, some users prefer browsing categories or scanning article titles. The chatbot works best as an addition to your existing search, not a replacement for it.
We set up the chatbot to prioritize the latest version of any document. If your docs have version-specific content (like API v2 vs v3), we can configure the chatbot to ask which version the user is on, or default to the latest. When you update or deprecate an article, the chatbot's knowledge base syncs automatically. For content that should no longer be referenced, we remove it from the chatbot's source material entirely so it can't surface stale information.
The chatbot retrieves answers directly from your actual documentation and cites its sources, so users can verify. It doesn't generate answers from general knowledge. That said, no AI system can guarantee zero errors. We build in response validation checks to reduce inaccurate answers, and every response links back to the source article so there's always a paper trail. If the chatbot isn't confident, it says so rather than guessing.
We'll build a working demo using your documentation, help desk, or knowledge base. See it answer real questions before committing to anything.
No commitment. No sales deck. Just a real conversation about your use case.