An AI assistant connected to company data is more than a chatbot. Reliable use depends on clear metric definitions, controlled access to source data and a way to verify each answer.
A question is mapped to a defined data model. The system calculates the relevant measure and then explains the result. Complex questions still need testing to confirm that the assistant interpreted them correctly.
Useful answers identify the period, metric and data source. For example: “₾812,000, ERP, October.” Users can then compare the result with the original report.
The assistant needs to understand internal terms, abbreviations and the company’s definitions of key measures. These are documented in the model, instructions and test questions.
The assistant should follow the organisation’s access rules. Hosting region, data retention and AI-provider terms depend on the chosen architecture and contract and should be reviewed before implementation.
Start with a reliable data model, 10-20 real questions and a person responsible for checking results. Existing Power BI models may be reusable after a technical review.
Tell us what you need to measure and where the data lives. We will review the request and outline a practical next step.