AzureOpenAI – Create | QualiWare Center of Excellence

Azure OpenAI is a Microsoft Azure service providing access to OpenAI models and tooling for building intelligent applications (NLP, computer vision, deep learning). QualiWare AI uses this service for its conversational and retrieval features.

Required Azure Role

Either one of these built-in roles (or a custom role with equivalent permissions):

Owner — full access including role assignments
Contributor — manage resources (no role assignments)

If role assignment is needed with Contributor, also grant User Access Administrator.

Azure Administration Tools / Interface

This guide uses the Azure Portal and a manual creation process.

Create and Manage Steps (Azure Portal)

Go to Azure OpenAI and click Create.

Go to the Networking section. Ensure settings comply with the customer’s Azure policy and allow access from QualiWare and the Azure App Service hosting the QualiWare bot application.

Tags are optional. Proceed to Review + create and then Create to provision the service.

Deployment Model

QualiWare AI Agent and QualiChat require the following models to be deployed:

gpt-4o
text-embedding-ada-002

Deploy Models (Azure AI Foundry)

Open the Azure AI Foundry portal and go to Deployments. (You can find the portal link from the Azure OpenAI service home page.)

Click Deploy model and choose to deploy a Base model. Search for the models listed above and confirm deployment.

Repository Explorer

From the repository explorer you can explore and search content in the repository. The repository explorer enables the user to search for a specific object type, list details, and see selection in the preview window. In addition to finding the relevant object fast, the repository explorer also provides easy access to edit funtions, and a whole set off options from the content menu including visualizations, and relations to the object.

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.

API Architecture Metamodel

An Application Programming Interface (API) is a construct that enables communication between systems. Integration between systems in complex environments continues to be a business priority to support automation activities. An API can be purpose-built for a bespoke integration (typical of legacy systems), or alternatively a standard connector can be developed between industry standard systems such as ERP’s and Service Management platforms. Managing these integrations becomes a complex operational task as updates and new releases to the integrated systems (and enabling technologies), can lead to intensive release management and testing activities. Security is also of utmost concern when managing integrations as the API provides a potential entry-point from either system integration direction – the API has become a preferred target for malicious attacks on systems and networks.