Best Practices in Knowledge Management

This guide outlines the best practices and operational workflows for establishing a robust Knowledge Management system. Following these standards ensures that your AI-driven bot provides accurate, relevant, and secure information to your employees.

1. Content Strategy & Selection

To maintain a high-quality knowledge base, focus on high-value content while eliminating "noise" that can confuse the system.
Docs: Best Practices for Content

Scope & Format

• Target Content: Focus on departmental knowledge such as HR and IT. Avoid syncing redundant information or departments like Procurement unless specifically required.
• Supported Formats: Use .pdf, .ppt, .docx, and .html.
• Excluded Content: It is recommended to not sync .xlsx, images, or handwritten documents, as these often contain "garbage" data or unstructured content that is difficult to parse.

Documentation Standards

[!TIP] Pro Tip: Always include external links to official policies or source sites. This allows employees to verify information and provides additional context for complex queries.

2. Technical Configuration: Metadata & Permissions

Ensuring the right people see the right information at the right time.

Permissions Management

Security is paramount. You can use base system permissions or platform-converted permissions from metadata.

• Action Required: Always ensure the "Fetch permissions" toggle is enabled when adding a new connector to maintain data privacy.
  Docs: Sharepoint

Audience Creation from Metadata

In cases where permissions are not managed properly in your source Knowledge Base (e.g., SharePoint), it is recommended to create an audience using metadata.

The Dynamic Audience Mapping feature introduces an Access Control step within the Connector Setup Wizard, enabling administrators to govern document visibility by mapping user attributes, such as Department or Country, directly to document metadata.

• Metadata Tagging: The system assigns specific audience identifiers to documents.
• Dynamic Filtering: Search results are filtered at the time of query based on the user's current profile.
• Real-time Updates: This architecture allows for access updates (e.g., an employee changing departments) without requiring a full re-sync of the knowledge base.

3. Quality Assurance & Testing

Before going live, use these built-in tools to audit your knowledge base for accuracy and redundancy.

Conflict Analysis

Identify duplicates or stale information by selecting folders (up to 1,000 articles).

1. Run the analysis to find conflicting info.
2. Correct the source document at the connector level (e.g., in SharePoint).
3. Re-check the conflict status to ensure a clean deployment.
   Docs: Conflict Analysis

Smart Testing (Automated Audit)

Smart Testing is an LLM-driven tool that measures bot accuracy before launch.

• The Process: The system generates Q&As from your uploaded docs, tests them against the bot, and provides an accuracy score (0–100%).
• Evaluation Criteria: Content Accuracy, Completeness, and Relevance.
• Limits: Up to 100 articles per run; 1,000 cumulative test cases per day.
  Docs: Smart Testing

4. UAT to Production Workflow

Use the User Acceptance Testing (UAT) environment for incremental testing of new content within your Knowledge Base. This applies to all integrations (e.g., SharePoint, Google Drive) by utilizing a secondary account with the same credentials. The KM dashboard allows you to manage up to five such instances for incremental data testing. Docs:Managing Multiple Instances of a Connector

Here is an example of such workflow for SharePoint integration.

The Workflow

1. Connect: Add a new site (e.g., a specific site rather than the whole Tenant) in UAT.
2. Test: Validate the content and bot responses thoroughly.
3. Deploy: Move the validated content to Production.

Deployment Options