Curate Content for AI Agent
Updated
Use well-structured, high-quality content to improve the accuracy and relevance of AI Agent responses. This article describes the supported content sources, recommended content formats, and best practices for preparing knowledge used by Retrieval-Augmented Generation (RAG).
Who Should Use This Feature?
This information is intended for:
- Administrators configuring content sources for AI Agents.
- Teams creating or managing knowledge content.
- Organizations preparing knowledge repositories for AI-powered responses.
Choose a Content Source
AI Agents support multiple content sources. Select the source that best matches your content management requirements.
Knowledge Base Articles
Use Knowledge Base articles when you need to manage large volumes of structured content.
Knowledge Base articles are recommended when:
- Content is updated frequently.
- Automatic synchronization is required.
- Content is maintained in a centralized knowledge repository.
Documents
Use documents when content is not available in a Knowledge Base.
Document-based content:
- Requires manual upload.
- Must be maintained manually.
- Does not support automatic synchronization.
Q&A Pairs
Use Q&A pairs for static information that requires predefined responses.
Q&A pairs are suitable when:
- Questions and responses are known in advance.
- Responses should be returned as authored.
- Content does not exist in Knowledge Base articles or documents.
Ensure each question represents a specific topic and includes common variations users may ask.
Language Requirements
To maintain consistent retrieval results:
- Use a single language across all content sources within an AI Agent application.
- Use English whenever possible.
- If English is not used, ensure all content is authored in the language supported by the AI Agent.
Note: Languages that use Latin-based scripts, such as English, French, and Spanish, generally provide higher retrieval accuracy. Languages such as Arabic, Chinese, and Japanese may experience lower retrieval performance.
Prepare Knowledge Base Content
Knowledge Base articles are the preferred content source for AI Agents.
Supported Content
Knowledge Base articles support:
- Plain text
- Content blocks
- Content variables
- Tables (feature-controlled)
- Images (feature-controlled)
Unsupported Content
The following content types are not supported:
- Videos
- Audio files
- GIFs
- Embedded documents
- External hyperlinks
Note: AI Agents do not retrieve or index content from linked webpages.
Best Practices
When creating Knowledge Base content:
- Use clear and descriptive headings.
- Write in complete sentences.
- Organize information into logical sections.
- Keep content concise and easy to understand.
- Avoid fragmented or disconnected content.
Synchronize Knowledge Base Content
Knowledge Base content can be synchronized automatically based on configured filters and sync schedules.
For more information, see Add Content Sources – Knowledge Base.
Prepare Document Content
Use documents for manually maintained content.
Supported Content
Documents support:
- Plain text
Limitations
Consider the following limitations when using documents:
- Large tables may reduce retrieval quality.
- Images are not processed.
- Videos, audio files, GIFs, and embedded documents are not supported.
- Linked content is not indexed.
Best Practices
To improve retrieval quality:
- Use simple formatting.
- Structure content using headings and sections.
- Write clear, complete sentences.
- Avoid complex layouts and heavily formatted content.
Prepare Q&A Content
Use Q&A pairs when responses should be returned exactly as authored.
Create Questions
When creating questions:
- Use clear language.
- Focus on a single topic.
- Include common user variations.
Create Answers
When creating answers:
- Provide accurate information.
- Keep responses concise.
- Avoid combining multiple topics in a single answer.
Control Content Usage with Topic Tags
Use topic tags to control how content is used by AI Agents.
Topic tags help:
- Organize content by subject.
- Improve retrieval relevance.
- Restrict content to specific use cases when required.