Global industrial technology manufacturer
Conversational AI, agentic workflows and model governance
10,000Global users on the platform
60%+Reduction in manual monitoring
8Production models under governance
Governance first was not caution. It was the only way the agentic work got approved to run at all.
The situation
Insight turnaround was measured in days. Analysts fielded the same questions repeatedly, and the people who needed answers were not the people who could write a query.
What I did
- Architected a RAG based conversational platform on AWS and Databricks, giving governed natural language analytics to the business rather than a new tool to learn.
- Established a model governance framework on Databricks Model Registry and MLflow: versioning, lineage, performance monitoring and drift detection.
- Then, and only then, deployed agentic workflows for customer service and sales operations, with authority boundaries and rollback defined before anything ran unsupervised.
What it produced
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