In the world of generative AI, knowledge base management isn't just a backend task—it's the basis for ensuring your AI assistant delivers accurate, up-to-date, and actually helpful responses. 

In our latest live product demo (check out the whole series if you’re curious!), Ixchel and Mercer pulled back the curtain on how to manage and optimize your knowledge base.

Whether you're new to AI knowledge bases or looking to up-level your RAG (Retrieval Augmented Generation) setup, this demo was packed with actionable best practices and ideas.

In this post, we’ll discuss a little bit about knowledge base management in general and go over some main takeaways from the demo.

If you’d prefer to listen or watch, you can just go ahead and scroll down to the recording below! 

Let’s get started.

Why knowledge base management matters

At its core, knowledge base management is the backbone of any successful AI assistant strategy. It ensures that your AI is grounded in accurate, relevant, and consistently updated information. 

Whether you're building a customer-facing support bot, an internal operations assistant, or a learning companion, what the assistant "knows" is only as good as what you feed it.

Poorly maintained or disorganized knowledge bases often lead to terrible user experiences, misinformation, and time-consuming escalations. 

On the other hand, a well-managed KB:

• Improves trust by ensuring consistent, fact-based answers
• Reduces support volume by enabling self-service for customers or internal teams
• Accelerates onboarding for new employees or users
• Prevents AI hallucinations, especially when paired with Retrieval Augmented Generation (RAG) techniques

RAG plays a crucial role here. Rather than depending on a model’s static memory, Crescendo uses RAG to dynamically retrieve information from your KB at the moment a user asks a question. 

Ixchel likened it to an open-book test: instead of relying on what the AI “remembers,” it looks up the correct, current info—just like flipping to the right chapter in a manual.

This approach allows your assistant to scale reliably with your business, ensuring it can evolve as your product, policies, or audience grow. 

And as your content changes, maintaining and curating your knowledge base becomes even more critical—because the better your KB, the better your assistant performs.

Setting the stage: a League of Legends assistant

To keep things cool (in a nerdy way—our favorite), Ixchel built a League of Legends–themed assistant tailored to help new players. She walked through:

• Setting the assistant’s tone and behavior (yes, it had delightful in-character responses like “Welcome to the Summoner’s Rift!”).
• Adding context and restrictions to keep responses on-topic.
• Injecting engagement, decline, and handoff messages inspired by in-game lore.

Even though the assistant was created for entertainment, it perfectly demonstrated the principles of structured knowledge base management.

Building and organizing your knowledge base

Effective knowledge base management starts with clear organization and purposeful structure. Whether you're working with a product help center, training materials, or an internal operations guide, the way you build your KB directly impacts how well your AI assistant can retrieve and present information.

In the demo, Ixchel walked through the setup for her League of Legends–themed assistant, showing how Crescendo makes it easy to add documents manually, scrape structured web pages, or sync entire help centers. 

But these tools are only powerful if the content they access is clean, consistent, and well-labeled.

So, here are some essential best practices for structuring your knowledge base:

• Use unique and descriptive document names: These serve as identifiers in the backend and feed into the vector index used for retrieval. Ambiguous or duplicate names can create confusion or retrieval errors.
• Add clear titles and summaries. The title is what you (and your team) will see at a glance, while the summary provides quick context about the document's content.
• Tag everything intentionally: Tags allow for content segmentation, filtering, and cue-based triggers in many AI platforms. They’re also super valuable for analytics and QA.
• Format for machines and humans: Use headers, bullet points, short paragraphs, and consistent terminology. This not only makes documents easier to read and edit, but also improves the AI’s ability to chunk and retrieve meaningful information.
• Keep content scoped to the assistant’s purpose: Irrelevant or overly broad content can dilute the assistant’s responses and lead to off-topic answers. Always ask: “Is this document necessary for what my assistant is supposed to do?”

Ixchel also emphasized the value of having a system in place outside the platform—such as a shared Google Drive or folder hierarchy—where your raw source content is stored, curated, and version-controlled. 

This ensures your team knows where the truth lives, especially if you're regularly updating or expanding the assistant's capabilities.

Whether you're supporting gamers, employees, or customers, strong knowledge base organization is a force multiplier. It enables your AI to answer faster, better, and more accurately—and it gives your team the foundation to grow and scale your assistant over time.

Importing knowledge: web scraping & help center sync

To expand the assistant’s knowledge, Ixchel demonstrated two powerful methods of importing content:

1. Web Scraping

Useful for structured wiki-style pages (like champion bios), but less effective for dynamic, iframe-heavy websites. Ixchel advised:

“Know exactly what you want to get from a website before scraping. Format matters.”

2. Zendesk Help Center Sync

This was the showstopper. With just the subdomain (e.g., riotgames.zendesk.com), Crescendo can ingest a full public-facing Help Center, automatically tagging and indexing all articles.

This enables large-scale, fast-loading knowledge bases without requiring an API integration—perfect for customer support use cases.

Internal FAQs: plugging gaps with guardrails

To handle questions that fall outside existing content, Ixchel introduced the concept of an Internal FAQ. Instead of letting the assistant hand off queries it can’t answer, you can:

• Manually add known hard questions.
• Provide a predefined answer or redirect (e.g., link to an external site).
• Tag and categorize these for future tracking.

This approach adds another layer of reliability to your knowledge base management strategy, especially for frequently asked but hard-to-answer questions.

Avoiding pitfalls: conflicts & maintenance

One key takeaway: avoid conflicts between behavioral settings and knowledge base content. Ixchel recommended:

• Keeping behavioral logic in the assistant settings.
• Keeping informational guidance in the KB.
• Never mixing the two—this leads to contradictions and confusion.

She also reminded viewers that even with automation, human stewardship is essential. Regular audits, updates, and content ownership are critical for long-term success.

In conclusion

Knowledge base management doesn’t have to be intimidating—or boring. With tools like web scraping, structured document creation, and Zendesk integration, you can quickly build intelligent, dynamic assistants that scale with your business.

Whether you're helping gamers, customers, or internal teams, the secret to a great assistant is a well-structured, actively maintained KB. Crescendo makes that process not only easier but surprisingly fun.

Want to watch the whole thing in action? Here you go:

If you’re interested in utilizing the magic of AI and humans in your business, we can help! Get in touch—no strings attached.

And don’t forget to join us in all future demos—we’ll be touching on AI personalization, knowledge base management, AI dashboards, and much more. Check out our upcoming events here and come along!

‍