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Create and Organize Knowledge

Knowledge in Relevance AI serves as the foundation for your AI agents’ intelligence, enabling them to access relevant information when responding to queries or performing tasks. This guide will walk you through the process of creating and organizing knowledge in Relevance AI, empowering your agents with the context they need to deliver accurate, helpful responses.

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Understanding Knowledge in Relevance AI

Knowledge in Relevance AI is a powerful Retrieval Augmented Generation (RAG) solution that provides your AI agents with access to specific information beyond their pre-trained knowledge. By creating well-organized knowledge bases, you can:
  • Ground your agents’ responses in factual information
  • Reduce hallucinations and inaccuracies
  • Provide domain-specific expertise to your agents
  • Keep your agents updated with the latest information
Knowledge in Relevance AI can take many forms - from small snippets of information that guide your agents on what “good” looks like, to comprehensive databases of support FAQs, to connections with external tools and integrations that retrieve information from specific websites or documentation.

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Creating Knowledge Sources

Relevance AI offers multiple flexible approaches to create knowledge, accommodating various information types and sources:

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Manual Input

When you have specific information that isn’t contained in existing documents, you can manually create and structure your knowledge:
  1. Navigate to the Knowledge section in your Relevance AI dashboard
  2. Click “Create Knowledge”
  3. Select “Empty Table” as your source
  4. Name your knowledge base
  5. Add columns to structure your information (e.g., Question, Answer, Category)
  6. Enter your information directly into the table
  7. Click “Create” to save your knowledge base
This approach gives you complete control over the structure and content of your knowledge base, allowing you to create precisely tailored information resources.

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Upload Documents

When your information already exists in document form, you can quickly import it:
  1. Navigate to the Knowledge section
  2. Click “Create Knowledge”
  3. Select “Upload Files” as your source
  4. Choose the file(s) you want to upload (supported formats include CSV, PDF, Excel, JSON, and audio files)
  5. Configure parsing options if needed
  6. Name your knowledge base
  7. Click “Create” to process and import your documents
Relevance AI automatically processes these documents, extracting the relevant information and making it searchable for your agents.

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Extract Website Content

To incorporate information from websites:
  1. Navigate to the Knowledge section
  2. Click “Create Knowledge”
  3. Select “Website” as your source
  4. Enter the URL(s) you want to extract content from
  5. Configure crawling options (depth, specific pages, etc.)
  6. Name your knowledge base
  7. Click “Create” to fetch and process the website content
This method is perfect for incorporating information from your company website, documentation sites, or other online resources without manually copying information.

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Connect Third-Party Integrations

You can use third-party integrations as integrated Knowledge sources to ensure your Agents have access to the most current information across your entire technology stack. You can learn more about each of our supported integrated Knowledge sources below.

Google Drive

Use Google Drive as a source of Knowledge for your Agents

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Organizing Your Knowledge

Effective knowledge organization is crucial for ensuring your agents can quickly find and use the right information. Here are strategies for organizing your knowledge in Relevance AI:

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Structured Tables

For FAQ-style knowledge or structured data:
  1. Create clear column headers that describe the information (e.g., “Question,” “Answer,” “Category”)
  2. Use consistent formatting within each column
  3. Include metadata columns to help with filtering and organization
  4. Consider adding tags or categories to group related information

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Document Chunking

When importing documents:
  1. Configure appropriate chunking settings to break down large documents into manageable pieces
  2. Balance chunk size - too small may lose context, too large may dilute relevance
  3. Consider overlapping chunks to maintain context across sections
  4. Use metadata to maintain relationships between chunks from the same source

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Knowledge Collections

Group related knowledge bases into collections:
  1. Create separate knowledge bases for different domains or purposes
  2. Use consistent naming conventions for your knowledge bases
  3. Consider the scope of each knowledge base - more focused bases often yield more precise results
  4. Document the purpose and contents of each knowledge base for team reference

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Enhancing Knowledge Quality

To maximize the effectiveness of your knowledge bases:

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Metadata Enrichment

Add contextual metadata to your knowledge entries:
  1. Include creation and update dates to track freshness
  2. Add author information for accountability
  3. Tag entries with relevant categories or topics
  4. Include confidence scores or verification status where applicable

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Knowledge Verification

Implement processes to ensure accuracy:
  1. Regularly review and update your knowledge bases
  2. Set up workflows for subject matter experts to verify information
  3. Track usage patterns to identify frequently accessed or potentially problematic entries
  4. Implement version control for important knowledge bases

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Semantic Organization

Enhance retrievability with semantic approaches:
  1. Use consistent terminology throughout your knowledge bases
  2. Consider adding synonyms or alternative phrasings for important concepts
  3. Structure information in a question-answer format where appropriate
  4. Include examples and use cases to illustrate concepts

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Connecting Knowledge to Agents

Once your knowledge is created and organized, connect it to your agents:
  1. Navigate to your agent’s configuration page
  2. Select “Add existing knowledge”
  3. Select the knowledge set you would like to add
  4. Select how the agent should use this knowledge
    1. Add all to prompt: this option adds the entire knowledge set directly into the prompt every time the agent runs.
      • Best for small or simple data sets
      • Easier to use with no extra configuration needed
    2. Allow agent to search: this uses Retrieval-Augmented Generation (RAG), where the agent searches the knowledge set using a tool.
      • Best for large or complex data sets
      • More flexible and scalable
  5. Depending on the option you chose, you can now see the name of your knowledge set as a tool or knowledge set variable in your agent prompt.

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Advanced Knowledge Configuration

Fine-tune how your agents interact with knowledge:

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Retrieval Settings

Adjust how your agent searches for information:
  1. Configure the number of results returned for each query
  2. Set relevance thresholds to ensure only highly relevant information is used
  3. Adjust search algorithms between keyword-based and semantic approaches
  4. Configure whether the agent should use knowledge for all queries or only specific types

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Knowledge Prioritization

When using multiple knowledge bases:
  1. Set priority levels for different knowledge sources
  2. Configure fallback behavior when information isn’t found in primary sources
  3. Set up rules for resolving conflicts between different knowledge sources
  4. Consider creating specialized knowledge bases for specific query types

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Query Transformation

Enhance retrieval effectiveness:
  1. Configure query preprocessing to improve match quality
  2. Set up query expansion to include related terms
  3. Implement query classification to route different types of questions to appropriate knowledge bases
  4. Use feedback loops to improve retrieval quality over time

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Best Practices for Knowledge Management

To maintain effective knowledge bases over time:
  1. Regular Updates: Schedule periodic reviews to keep information current
  2. Version Control: Track changes to your knowledge bases, especially for critical information
  3. Usage Analytics: Monitor how your agents use knowledge to identify gaps or improvement opportunities
  4. Feedback Integration: Create processes to incorporate user feedback into your knowledge bases
  5. Documentation: Maintain clear documentation about your knowledge structure and organization
  6. Quality Control: Implement validation processes for new knowledge entries
  7. Scalable Structure: Design your knowledge organization to accommodate growth
  • Access Knowledge: Learn how to configure how your agents and tools access and use your knowledge bases.
  • Enrich with Tool: Discover how to enhance your knowledge bases with additional context using tools.
  • Advanced Knowledge Retrieval: Explore advanced techniques for optimizing how your agents retrieve and use knowledge.