Application Refactoring
simplify a compute-heavy healthcare data ecosystem spread across AWS, Databricks, and custom software so OM1 could deploy ML code faster, reduce maintenance, and keep PHI redaction efficient.
Reported impact
OM1 achieved 75% savings in processing costs using Snowpark Container Services to redact PII data and 100M+ clinical records redacted in less than 30 minutes to protect patient privacy.
OM1 uses Snowflake, Snowpark, and Snowpark Container Services on Snowflake to simplify a compute-heavy healthcare data ecosystem spread across AWS, Databricks, and custom software so OM1 could deploy ML code faster, reduce maintenance, and keep PHI redaction efficient. Patient, claims, and clinician-note data are centralized in Snowflake so data engineers, clinical researchers, and ML teams can work from a faster, more reliable operating view. Snowpark keeps transformation and application logic close to the governed data instead of forcing the team to move workloads into separate compute environments. Keeping ingestion, storage, transformation, and governed access on one platform reduces handoffs, simplifies operations, and makes it easier to reuse trusted data across analytics, reporting, and AI. OM1 achieved 75% savings in processing costs using Snowpark Container Services to redact PII data and 100M+ clinical records redacted in less than 30 minutes to protect patient privacy.
patient, claims, and clinician-note data flow into Snowflake, Snowpark, and Snowpark Container Services; curated data, reports, and model outputs are then served to data engineers, clinical researchers, and ML teams.
100M+ clinical records redacted in less than 30 minutes to protect patient privacy
75% savings in processing costs using Snowpark Container Services to redact PII data
OM1 achieved 75% savings in processing costs using Snowpark Container Services to redact PII data and 100M+ clinical records redacted in less than 30 minutes to protect patient privacy
The sheer size and complexity of OM1’s data sets require a reliable, scalable platform to meet the industry’s rigorous demands for privacy, accuracy and credibility
To deliver real-world insights from bench to bedside, OM1 moved its complex ecosystem spread across AWS, Databricks and custom software — and discovered newfound simplicity and efficiency in the process
Review how this reference was scored and trace each normalized claim back to its documented source.
Scoring methodology
Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.
Traceability
Field coverage shows which facts each source supports. Dates are shown only when documented by the source.
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