Evaluation-First AI Agents: How Zepto Scales Customer Support on Databricks and MLflow

This post details the implementation of evaluation-first AI agents to scale customer support on Databricks and MLflow. It highlights Zepto's approach to agent development, focusing on rigorous evaluation to ensure performance and cost-effectiveness. The post likely describes the architecture of these agents, the evaluation methodologies employed, and how MLflow is used for tracking experiments and managing agent deployments. It also touches upon the integration with Databricks for scaling these agents, implying a focus on production readiness and operational efficiency.