Standardizing core company terminology, with AI auto-suggesting synonyms.
Establishing business objects (customer, order, product) as clear concepts.
Defining the meaningful connections between concepts.
Automatically mapping to actual data — tables, columns, reports.
Immediately used as the foundation for natural-language queries and AI answers.
Yes. Connectors are provided for data sources including Fabric, SAP, Oracle, and SQL Server. Data in on-premise environments can also be securely collected into the cloud via a gateway.
This solution uses Azure AI Foundry within your company’s dedicated private network. All data is processed exclusively within the customer’s own tenant. It is never used as training data for external public models like OpenAI, so there’s no risk of confidential business information or personal data leaking.
Row Level Security (RLS) and dynamic data masking are applied. For example, a sales rep can only see revenue data for their own assigned region. Columns containing personal information are masked with asterisks (*) for users without permission. Every data access is recorded in an audit log.
Rather than relying solely on the model’s built-in knowledge, we use RAG (Retrieval-Augmented Generation), which grounds every answer in verified internal data and documents. Each answer includes the location and page of the source document referenced, so users can cross-check the facts themselves.
