QualiWareAI Help | QualiWare Center of Excellence

QualiWareAI Agent

I’m QualiWareAI agent, your assistant to help you with instant access to QualiWare knowledge. You can ask me questions about your models, processes, diagrams, any other information from the QualiWare repository, or general domain knowledge.

Use of QualiWare AI Agent

1) Copilot

Open Copilot and either start a chat with QualiWareAI or mention it in any Copilot conversation.

You can also use voice-to-text to ask your question, and use the built-in prompts to select a repository or clear history.

Note: At this stage, QualiWareAI supports text-based queries only. Files, images, and other media inputs are not yet supported.

2) Teams Chat

You can chat with QualiWareAI directly in Microsoft Teams.

Click the Select Repository prompt and then the send icon to view and choose from the repositories permitted by the administrator.

3) Group Chat in Teams

Invite the QualiWareAI agent into group chats or meetings and engage with it by asking questions directly. Team members are encouraged to interact with the agent during the conversation.

How to interpret the answers

QualiWare Knowledge: content derived from the connected QualiWare repository.
AI General Knowledge: information generated from general AI knowledge that is not sourced from the QualiWare repository.

Ontologies in QualiWare

This page is intended to help users model knowledge using the QualiWare GOWL implementation delivered in release 10.8 of QualiWare.

Visualization

QualiWare X contains a 3D visualization feature. The feature can be used on any object or be available in relation to queries and lists. A visualization creates a “solar system” with the selected object(s) in the center.

Clustering

Clustering provides users with a new way of interacting with content in their repository. It provides an enhanced analysis capability directly from the 3D Visualizer by logically grouping objects based on their relationships, concepts, and definitions. Filters can be applied to the clusters through the table-based view using existing functionality to focus analysis efforts (for example only clustering objects that are related to a risk with a high impact). The number of clusters can also be defined by the user to provide a broader or more concise result.