A new knowledge base article has been published on our support portal.
Overview
AI Large Language Models (LLMs) are inherently probabilistic, making them less suitable for scenarios requiring fast and consistently 100% accurate results. However, integrating a Dataverse Agent with the North52 business rules engine offers a powerful solution—enabling the use of AI capabilities while maintaining strict accuracy and deterministic outcomes.
Here’s why deterministic rules are essential for your Dataverse AI Agent:
- Compliance: Ensure regulatory requirements are always met
- Data Quality: Maintain consistent data validation and formatting
- Business Logic: Apply your organization’s specific rules without exception
- Reliability: Remove uncertainty from critical decision points
This article shows you how to get deterministic rule-based outcomes in your Dataverse Agent.
Rules for Credit Card Eligibility
In our simplified example we have rules in a North52 decision table Formula which determines credit card eligibility for 3 types of card Platinum, Gold and Silver. The thresholds are specified across three decision sheets, one for each card type. These decision tables are shown in the Decision Suite Solution section below.
| Rule # | Description |
|---|---|
| 1 | Customer is eligible for a Platinum card if they meet the Annual Income, Total Assets and Credit Score thresholds as defined in the Platinum Rules Decision Sheet. They will be allocated a credit limit of 10% of their annual income. |
| 2 | Customer is eligible for a Gold card if they meet the Annual Income, Total Assets and Credit Score thresholds as defined in the Gold Rules Decision Sheet. They will be allocated a credit limit of 10% of their annual income. |
| 3 | Customer is eligible for a Silver card if they meet the Annual Income, Total Assets and Credit Score thresholds as defined in the Silver Rules Decision Sheet. They will be allocated a credit limit of 10% of their annual income. |
| 4 | If no thresholds are meet the eligibility result is false. |