A chatbot is only as smart as the data you provide
We’ve all met the chatbot that replies “I’m not sure I understand your question” to every request. Most of the time, the issue isn’t AI. It’s the data it was fed.
A chatbot can’t improvise knowledge. It learns solely from the text you give it: your content, your structure, your consistency. When that content is messy, repetitive or unclear, the chatbot mirrors it.
This guide explains how to build a knowledge base your chatbot can actually learn from: clean, clear and structured public text that helps it answer like a pro.
Quick note: examples below show how this works in Murai, but the principles apply to any chatbot.
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What is a knowledge base?
A knowledge base is your company’s shared memory - a single, structured place for all public information your chatbot should know. It keeps answers consistent and easy to find, whether they come from FAQs, documentation or your business website.
Step 1: Start with the right data and content
Before uploading anything, decide what your chatbot should know - and what it shouldn’t.
If you’re working with internal documents or process-heavy files that can’t be shared publicly, that’s where an AI Assistant could be a perfect solution for you. It searches through private data, answers employee questions, and lightens everyday workloads - read more about it here.
Chatbots are designed to share your public-facing information with customers, not to store private or internal data. That means everything you feed them should already be safe to appear on your website. Pricelists, public schedules, product catalogues, etc.
Good sources:
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Help center pages, FAQ pages, product documentation.
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Blog posts, user manuals or setup guides that explain your service.
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Public PDFs, Markdown files or website URLs with relevant information.
Avoid:
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Internal documents, emails, or customer data.
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Draft or half-finished documents, full of comments.
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Scanned images or screenshots of texts.
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Heavily formatted layouts (tables, slides) or mixed-language docs.
Pro tip: If you wouldn’t publish it on your website, don’t feed it to your chatbot.
For a detailed overview of how to upload your data (including URLs and PDFs), check Murai Docs here.
Step 2: Keep it simple, structured and scannable
A chatbot reads structure, not style.
It doesn’t see fonts or colors. It reads the logical flow of your text. Headings, bullet points, and short paragraphs help it understand what’s important.
For best results, keep your entries concise: 8-10 sentences or roughly 1,000 characters per paragraph. Each section should express a single idea or answer a specific question, allowing your chatbot to retrieve it accurately.
Do:
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Use clear section titles (e.g., “Refund policy” instead of “General info”).
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Break long paragraphs into smaller chunks, one idea per paragraph.
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Keep terminology consistent (“customer” vs “client”).
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Use lists or tables for processes and comparisons.
Don’t:
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Paste messy copy from Word or Google Docs without cleaning formatting.
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Upload multiple versions of the same file.
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Mix topics in a single document (“returns” + “shipping” + “warranty” in one file).
In Murai, every file becomes a separate searchable block in your knowledge base. Duplicates or half-finished docs only confuse the model.
Why this matters:
Murai’s parser reads text line by line. Each paragraph should form a complete, self-contained idea. Walls of text or fragmented sentences make it harder for the chatbot to retrieve the right context later.
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Example of a bad input:
“Our warranty covers parts, labor and accessories under standard conditions. Standard conditions may vary per product. See below for exclusions.”
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Better input:
“Our warranty covers parts, labor, and accessories under standard conditions.
Standard conditions vary by product type.
Exclusions are listed under “Warranty limitations.”
Same information, just better for humans and chatbots to understand.
Step 3: Format before uploading (clean text wins every time)
Before uploading your files or URLs, spend a few minutes formatting them properly. It’s a small step that makes a huge difference in retrieval accuracy.
Quick checklist:
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Prepare your content as PDFs or text in Markdown*.
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Remove unnecessary headers, ads, and footers.
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Keep filenames clear and consistent (e.g., refund_policy.md, setup_guide.pdf).
Consistent formatting helps Murai split content into clean data chunks, making it easier to fetch precise answers instead of vague summaries.
*Markdown is a simple way to format text using symbols (# for titles, * for bullet points) so your content stays clean and readable.
Step 4: Test in small batches
When you upload content, your chatbot processes and indexes it for retrieval. Large, unfiltered dumps of text (mixing products, policies, and marketing materials) can slow learning and reduce precision.
Start small:
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Upload one category (e.g., Shipping & Returns).
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Test a few real-world questions (“How do I return an order?”, “What if my shipment is delayed?”).
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Adjust the source text if needed.
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Add the next category once you’re done and happy with results.
This iterative approach mirrors how Murai works under the hood: retrieving context from smaller, well-defined segments rather than one massive blob of text.
Step 5: Test your chatbot like a user, not a developer or a business owner
Once your knowledge base is uploaded, it’s time to test it properly - not with sterile, technical prompts but with the kinds of questions your users actually ask:
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“When will my order #3194 arrive?”*
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“Can I get a refund if I opened the product?”
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“Do you ship internationally?”
If answers sound vague or even incorrect, check for these common causes:
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The relevant info is buried too deep in the document.
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Two sources contradict each other.
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Formatting makes similar phrases look unrelated.
Fix the text, re-upload, and test again. Training is iterative: every correction teaches the chatbot to respond more precisely next time.
*Personalized questions like this are possible with advanced integrations through the API.
Step 6: Maintain and refresh regularly
Like every real brain, your chatbot’s knowledge fades without updates.
Keep it current by retraining whenever you change product descriptions, prices, or terms.
In Murai, you can simply upload a new version of a file or URL and trigger retraining. The model refreshes automatically without forgetting previous knowledge.
Maintenance checklist:
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Review top chatbot questions weekly: not only to see how the chatbot is doing on its own but also to spot where your users are losing sleep over your product. It may help you to further explain your service also on the website.
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Add missing topics: Based on real conversations and customer input, you can easily fill the gaps without wondering.
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Remove outdated or duplicated content: Chatbot can be a great helper in identifying what is no longer up to date on your website, your pricelists or offers just by combing through their answers.
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Re-upload public files after website updates: With every new addition to your product features, website subpage or policy changes don’t forget to update your chatbot’s training data.
Common mistakes to avoid
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Uploading before editing. Clean and simplify your text first.
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Mixing internal and public data. Keep private content out of public chatbots.
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Skipping tests. Always validate responses before deploying.
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Ignoring updates. Even the best data goes stale if no one maintains it.
Murai also provides a Knowledge base API, allowing you to connect automation tools like n8n (an open-source workflow automation platform) to keep your chatbot’s data up to date automatically.
Why all this matters
A well-structured and well-kept knowledge base turns a chatbot from a glorified FAQ bot into a reliable support teammate.
Users get clear, context-aware answers. Your support team saves hours of random mailing with clients. Your brand sounds trustworthy instead of robotic.
Whether you’re launching your first chatbot or refining an existing one - start with your content. The step-by-step guidance in the Murai Docs will help you upload the best version of the content you have.
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Structuring your knowledge base - a detailed guide
AI doesn’t invent clarity - it learns it from you.
While chatbots handle public content beautifully, AI Assistant is designed for what stays behind the login - internal processes, technical docs, and company know-how. Together, they make both sides of your organization searchable.
Give it a try
You don’t need to be a developer or tech-savvy to build a great chatbot.
But if you are going to do it, do it right - and reap the rewards of a chatbot that’s genuinely helpful?
Try Murai, build your first chatbot in minutes and refine its knowledge base today.
Or, explore what AI can do for your business and apply for a free AI consult - you might be surprised how many solutions are already aligned with your company’s goals.
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