Knowledge Management Permissions: Query Metadata

This article explains how to use query metadata to control the data and knowledge scope that AI assistants can reference.

Feature Description

When deploying an AI conversation system, organizations typically need fine-grained control over the available scope of "Knowledge Bases / AI Assistants / Conversation Platforms" based on user permissions and usage requirements.

In MaiAgent, you can use query metadata attached to different conversation / identity levels to determine "what content this person / this conversation can reference."

What Is Query Metadata?

Query metadata is a set of dynamic conditions that define the query scope. It can specify which "knowledge bases, FAQs, and documents matching tag conditions" a user can query on a given conversation platform.

It does not replace roles or contacts; rather, it enables these identities to "function conditionally," achieving conversation-level least privilege control.

Roles / Contacts / Conversations are containers; query metadata is the condition settings that actually control the visible scope

Learn more from the following articles:

• Contacts

• Role Permission Management

Permission Level Concept

Before constructing a service, the Agent verifies all available knowledge bases through query metadata at different levels. The permission level reference order is as follows:

AI Assistant > Conversation Platform > User (Conversation / Contact / Role) > Query Metadata > Query Permissions

You can specify permissions at each level using the graphical interface or JSON format

See the following documentation for instructions:

1. Getting Started — Using the "Query Builder"

2. Technical Manual: JSON Interface Configuration Guide (Contacts, Web Chat Embed Settings)

• Contacts / Roles are identity containers

• Conversations correspond to internal conversations where you can control the knowledge bases used through filtering

• Query metadata is the "set of filter conditions" actually applied during conversations

Document Filtering Condition Level Hierarchy

Through layer-by-layer transmission, query metadata becomes the actual decision-making basis for AI response logic

Practical Use Cases

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Summary: The Value of Query Metadata for Enterprises

🎯 Multi-dimensional identity cross-control (role + region + product line)

🎯 Real-time query control: No need to duplicate assistants — just change the conditions to switch between scenarios

🎯 Flexible large-scale knowledge base management: Tags and knowledge bases can be split and authorized by scenario

Incorporate query metadata into your product architecture core to achieve maximum authorization flexibility with minimal configuration, ensuring knowledge security while improving conversation experience and operational efficiency.