Bring together clinical, claims, operational, and unstructured data into a single platform for streamlined access and analytics.
Ingest, normalize, and analyze data using FHIR, HL7, X12—built to support real-time interoperability and compliance.
Train and deploy machine learning models at scale to drive predictive care, disease risk detection, and quality reporting.
Meet HIPAA, HITRUST, and SOC2 standards with built-in governance, auditability, and fine-grained access controls.
Automate ingestion, standardization, and integration of high-volume healthcare operations data to reduce dependencies on legacy systems and manual workflows.
Leverage unified data products to predict member behavior, stratify risk, and enable proactive interventions across clinical and non-clinical touchpoints.
Accelerate deployment of ML models to personalize digital experiences and optimize cross-channel engagement strategies.
Centralized lakehouse + domain-owned data marts enabled faster insights, trusted metrics, and agile delivery at scale.
Our team includes Databricks-certified professionals with deep experience in healthcare-specific data engineering, analytics, and ML ops.
We’ve delivered HIPAA-compliant data lakehouses, interoperability pipelines, and predictive models for hospitals, payers, and digital health platforms.
Flexible engagement: embed our talent into your teams or let us own delivery from design to deployment with SLAs and defined milestones.
We reduce onboarding time with proven healthcare data templates and pre-built accelerators—so your team sees results in weeks, not months.
We bridge Databricks with Snowflake, Azure, AWS, Kafka, FHIR APIs, and healthcare-specific formats (HL7v2, X12, CCD)—no silos, no gaps.