Scrubbing sensitive notes required fragile external clusters. An embedded LLM now anonymizes data directly within the pipeline.
A healthcare technology company analyzes billions of clinical records across 350 million patients to provide real-world insights for researchers and pharmaceutical partners.
Critical patient details were buried in unstructured clinician notes, but processing this sensitive data required a fragile ecosystem of Spark...
“We were on a mission to simplify our entire ecosystem. While we had moved our data to Snowflake, we had a complex ecosystem of compute spread across AWS, Databricks and custom software. While this system worked, it came with fairly high cost and overhead. From a business perspective, it’s all about efficiency. We want our data engineers to spend their time innovating and solving hard problems, not maintaining platforms.”
Real-world data and AI analytics platform for healthcare and life sciences.
Cloud-based data warehousing, processing, and analytics platform.
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