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Integrating Agent BizOps with Data Governance: Generating AI Use Cases and Agents in Tavro, Identifying CDEs in DataHub with MCP Server

Mortgage Underwriting Agent for sub-650 credit scores in Tavro Agent BizOps, showing its role description and system instructions

In a previous blog, we used Tavro’s Open-Source Agent BizOps Platform to generate an AI Use Case and Agent to originate sub-prime customers with less than 650 credit scores. How do we integrate this back to the data governance program?

Please visit the Tavro GitHub repo for a detailed how-to on the DataHub integration.

In this blog, we demonstrate a use case to integrate Tavro with Datahub’s MCP Server:

  1. Prototyped AI Agent using Tavro
    To recap from the earlier blog, we prototyped the AI agent in Tavro.

    Sub-650 Mortgage Underwriting Agent prototyped in Tavro, with a blended score of 4.96 and its system instruction

  2. DataHub contains Critical Data Elements
    DataHub already contains Critical Data Elements such as Adverse Action Codes, Alternative Credit Indicators, Credit Score, Debt-to-Income Ratio, and Loan-to-Value Ratio within the Banking Glossary.

    DataHub Business Glossary Banking term group with five terms, including Credit Score and Debt-to-Income Ratio

  3. Prompt For Fetching Glossary Terms from datahub
    We prompted the Tavro AI Assistant to fetch the glossary terms from DataHub.

    Prompt asking Tavro to fetch glossary terms from the Banking term group in DataHub
    Tavro used the DataHub MCP Server to fetch the business terms from the Banking glossary.

    Tavro AI Assistant response listing five Banking glossary terms retrieved from DataHub through its MCP Server

NewerAgent BizOps: Where Governance Becomes Adoption
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