🚦Is Your KB Ready? A Quick Assessment Guide
Why assess Your Knowledge Base Before an AI Project?
Your Knowledge Base (KB) is the foundation of your AI Agents. Its quality, structure, and completeness directly impact:
How well your AI Agents perform
The accuracy of responses they provide
The complexity and timeline of your AI agents implementation.
Before proceeding with AI configuration, you need to assess what you already have and determine whether your documentation is AI-ready or requires improvement.
This guide will help you:
✅ Evaluate whether your existing knowledge is complete and structured enough for AI use. ✅ Identify gaps or issues that may affect AI accuracy. ✅ Understand the effort required to optimize your KB before integrating it with AI Agents.
Let’s go step by step!
Step 1: Do You Have the Necessary Content?
Before setting up your AI Agents, start by evaluating whether you have the necessary content for each topic they will cover.
To ensure AI Agents can provide accurate responses, it's essential to determine which information is truly relevant and valuable. The most effective way to do this is by identifying:
The most common questions your users ask.
The key information your chatbot should provide.
Existing documents that contain these answers.
Not all internal documents are useful for AI Agents!
Instead of uploading everything, focus on content that is structured and directly relevant to user interactions.
For example, legal documents, contracts, or terms & conditions are often written in complex legalese and may not be ideal for providing direct customer support.
If content is missing, it must be created first, which adds time and complexity to the AI implementation.
If your only available knowledge source consists of historical customer service tickets or chat logs, you’ll need to build a structured Knowledge Base from scratch, as these records often contain outdated, inconsistent, or irrelevant information that isn't optimized for AI processing.
Topic 1
✅ Yes
Proceed with content optimization & upload
Topic 2
⚠️ Partially
Fill in missing details or refine content
Topic 3
❌ No
Create content from scratch before proceeding
Where to Look for Existing KB Content
If you’re unsure whether your content already exists, check:
Internal Documentation (FAQs, product manuals, guidelines, training materials)
Customer Service Records (ticketing systems, chat transcripts, common inquiries)
Website Content (help center, blogs, knowledge articles, product pages)
Spreadsheets & Databases (services, product specs, pricing, inventory data)
Step 2: What is the Best Format & Integration Method?
After identifying what content is available, the next step is to assess whether the format of that content is suitable for AI Agents and determine the most appropriate integration method.
Key Factors to Evaluate
1️⃣ Content Complexity & Volume 2️⃣ Documents Structure and Format 3️⃣ Data Update Frequency
1️⃣ Content Complexity & Volume
Large and complex datasets should always be integrated via API rather than uploaded as static documents.
API Integration is ideal for managing complex data such as product catalogs (e.g. Google Sheets, Shopify) and large databases (e.g. customer records).
On the other hand, document uploads work well for simpler, static content like FAQs, troubleshooting guides, company information, and policies.
2️⃣ Documents Structure and Format
When assessing your content, it’s important to look beyond the file type and focus on what the document actually contains, and how well it’s structured and formatted for AI Agents to process.
✅ Best-case scenario → Content that is already structured and formatted for AI use is ideal. (For more details on the specific requirements and best practices, refer to Step 3.)
A great example is an FAQ document formatted in a table with question-answer pairs. This format is ideal because of its clear structure (e.g., Q&A pairs, easy for AI to parse) and minimal complexity, making it straightforward for AI Agents to retrieve and process the information.
❌ Worst-case scenario → Content that only exists on a website can be problematic.
Websites vary widely in structure, making it difficult for AI Agents to extract relevant information due to the presence of unrelated content, such as ads, sidebars, or inconsistent layouts.
We typically avoid scraping information from URLs, except for contextual company pages like "About Us" or "Contact."
The more structured and consistent your content is, the easier it will be for your AI Agents to extract useful information and provide accurate responses. If your content is messy or unstructured, it will require additional work to make it suitable for AI use.
3️⃣ Data Update Frequency
It's important to assess how frequently your data changes or needs to be updated.
Static data (e.g., FAQs, policies) → Document uploads work well for low volumes of data, while an API integration is more suitable for larger or complex datasets.
Dynamic data (e.g., pricing, stock levels) → API integration is best for real-time data that changes frequently. This ensures that AI Agents always retrieve the latest information and eliminates the need for manual updates.
Recap
By considering these three key factors - content complexity, structure/format, and update frequency - you can assess whether your content is in the ideal format and determine the best integration method for your AI project.
Content Complexity & Volume
API Integration for large or complex datasets (e.g. product catalogs, customer records)
Upload for simple, structured documents
Messy, unstructured content and complex data
Document Structure & Format
Structured content like Q&A tables, clearly formatted documents
Scraping from unstructured websites or scanned PDFs
Data Update Frequency
API Integration for real-time retrieval of frequently updated data (e.g., pricing, inventory).
Document uploads for content that doesn't change often.
Manual updates for frequently changing data
Step 3: Are Your Documents AI-Ready?
Now that you've assessed your content, it's time to dive deeper into ensuring that the documents or data you need to upload to the platform meet the requirements for effective AI processing. There are specific formatting and structural best practices to follow to ensure AI Agents can easily retrieve and process the information.
Use this checklist to determine if your documents or API data sources are properly formatted and structured for optimal AI performance.
AI-Ready Content Checklist
✅ Supported File Formats → Our platform supports: .pdf, .docx, .txt, .csv, .xlsx. ✅ Formatting & Structure → Information must be clearly structured. ✅ Language & Readability → Avoid complex jargon, use clear and concise language. ✅ AI Processing Compatibility → Ensure that files are machine-readable.
As an example, scanned PDFs are not AI-friendly because they aren’t machine-readable. Consider converting such files into editable text formats.
More specifically, you can find a checklist of best practices based on the file type in the table below:
All
Content is written in the same language as the AI workspace
Each document covers one clear topic instead of mixing multiple topics in a single file
Sentences are concise, clear and to the point, avoiding unnecessary explanations or specific jargon
Maintains a consistent tone and terminology throughout
URLs are explicitly written rather than embedded in hyperlinks
TXT
Keep plain text with clear Q&A pairs
Use Markdown formatting to structure the document with clear titles, subheadings
Use UTF-8 encoding for compatibility
Avoid excessive line breaks or blank spaces
DOCX
Use proper headings & subheadings
Ensure consistent formatting (bold, lists, tables)
Remove unnecessary images or embedded elements
CSV
Use two-column structure (Question/Answer or Key/Value)
No empty rows or unnecessary columns
Keep headers clearly labeled and formatted
XLSX or Google Sheet (via API)
Structure sheets with clearly labeled columns
Each tab should focus on a single topic
Avoid merged cells and excessive formatting
Best format for for product codes, IDs, or inventory data
Step 4: What Needs to Be Done?
After completing the assessment, you should now have clear next steps based on your KB’s status.
❌ Major gaps, no structured data
Build KB from scratch
High
⚠️ Some content is missing or incomplete
Create missing content
Reformat documents that are not structured properly for AI use
Medium
✅ KB is ready
Proceed with documents upload
Set up API integrations for real-time data retrieval
Low
Priority Recommendations
First, create missing content → Ensure at least one structured FAQ document in a Q&A tabular format (best for AI Agents).
If needed, set up API integrations → Especially for real-time or large, complex data sources.
Refine and optimize existing documents → Ensure correct structure, readability, and formatting.
Need Help?
📢 Feeling Overwhelmed? You don’t have to do this alone!
If you need assistance with managing a large volume of documents, automatically retrieving content from platforms like Google Drive, Confluence, or SharePoint, or optimizing and structuring your KB, we’re here to assist. Reach out to us, and we’ll ensure your KB is AI-ready with minimal effort on your part.
Guides on Integrating or Uploading your Content
By now, you should have a clearer understanding of the next steps and the work required to build your KB. To help you move forward, explore the following articles for detailed guidance on fine-tuning and uploading your KB content using the two available methods:
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