Anthropic’s existing ETL pipeline struggled to keep up with surging transaction volumes—frequently hitting API rate limits, causing data delays, and requiring daily manual intervention to stay on track.

With Data Pipeline, Anthropic accelerated month-end close by six days and eliminated ongoing engineering work. Stripe data now flows reliably into BigQuery, where hundreds of data models combine Stripe and business data to produce auditable financial records and reliable reporting for leadership and investors.

Cursor needed reliable access to Stripe data to close the books and track performance, but with a small engineering team, the company did not want to spend resources building and maintaining custom data infrastructure.

Data Pipeline syncs Cursor’s Stripe data into Databricks, powering performance dashboards for reporting on key metrics like revenue and churn. It also powers a billing operations dashboard, empowering the team to resolve complex billing inquiries and manage customer operations more efficiently.

ChowNow wanted to better understand profitability, margin, and unit economics at both the customer and transaction levels without having to build an API integration or share its data with an ETL pipeline.

With Data Pipeline, ChowNow’s Stripe data now flows into Snowflake, where the company can track chargebacks by restaurant, optimize ad spend with full visibility into the customer journey, and analyze net margin per restaurant to optimize its pricing strategy.

When exporting Stripe data to Snowflake via a third-party ETL, Lime kept running into data discrepancies—each one taking engineers up to two hours to investigate.

Data Pipeline resolved Lime’s data discrepancies, cutting delivery time from three days to one. Engineers no longer spend hours investigating mismatches, the finance team confidently reports on cash status and refunds, and the fraud team can build better models by combining Stripe risk scores with proprietary data.