Databricks Demonstrates Responsible AI For Telecom Agents

Databricks details responsible AI practices for agentic systems in telecom, demonstrating evaluation and governance using MLflow and LangGraph in a multi-agent customer churn case study. The blog outlines pillars—evaluation, transparency, fairness, robustness and governance—shows MLflow AI Evaluation Suite features like built-in judges and custom scorers, and includes code examples to operationalize continuous measurement. It emphasizes trust, safety and regulatory alignment, citing McKinsey's $250 billion telecom opportunity by 2040.