Case Study: People.ai cuts DevOps costs 20–30% and accelerates ML and data pipelines with Databricks

People.ai - Customer Case Study

People.ai delivers revenue intelligence for sales, marketing and customer success teams by capturing contacts, activities and engagement to surface every revenue opportunity. As the company scaled, its Python-based, DevOps-intensive data pipeline and vanilla Spark deployments generated significant operational overhead, made configuration changes and experimentation slow and risky, and limited collaboration between data engineers, scientists and analysts.

By adopting the Databricks Unified Analytics Platform on AWS, People.ai built end-to-end notebook workflows, optimized ETL and resource management, and established a low-disruption migration path from test to production. The change cut DevOps effort (20–30% savings), supported 30+ users in a collaborative environment, reduced manual work for experiments and batch jobs, improved security controls, and enabled faster data exploration for machine learning, NLP and streaming initiatives.

People.ai

John Wulf

Principal Engineer