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-90%
New data source onboarding reduced from weeks to hours
A healthcare analytics company needed to process and structure data from hundreds of disparate sources: EHR systems, lab reports, insurance claims, and research papers. Their manual data engineering pipeline was a bottleneck, taking weeks to onboard new data sources and frequently producing inconsistencies that required expensive manual cleanup.
We built an AI-powered data ingestion and transformation pipeline that automatically identifies data schemas, maps fields across sources, handles format variations, and flags anomalies for review. The system uses AI to parse unstructured medical documents, extract relevant data points, and standardize terminology using medical ontologies. New data sources can be onboarded in hours instead of weeks.
-90%
Onboarding Time
New data source onboarding reduced from weeks to hours
99.2%
Data Quality
Accuracy rate for structured data extraction
15x
Processing Speed
Faster data processing compared to manual pipeline
-70%
Engineer Time
Reduction in data engineering hours per source
“We used to dread onboarding new hospital systems. Now our AI pipeline handles the heavy lifting and our engineers focus on analysis instead of data wrangling.”
Dr. Amy L.
VP of Data, Healthcare Analytics
7 weeks
From kickoff to production deployment
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