Case Study: Laurel accelerates ML pipeline development with Astronomer’s Astro

Laurel doubles billing efficiency with Astronomer and Airflow

Laurel, a company dedicated to building trust in professional timekeeping, faced the challenge of managing massive amounts of data to power its machine learning models. Their ML team was previously bogged down by manual data extraction and ETL tasks, which slowed down their development velocity. They partnered with Astronomer to find a robust and scalable system to manage these pipelines.

By adopting Astronomer's managed Airflow solution, Astro, Laurel was able to automate its ML model retraining pipelines. This provided immediate impact by drastically reducing the time it takes to create a timesheet, which is a key external KPI. Astronomer's solution also greatly improved the team's internal development velocity, allowing them to test new hypotheses faster. The platform's auto-scaling capabilities efficiently handled increased load as Laurel onboarded more customers, supporting crucial business growth.

Laurel