Data Infrastructure That Healthcare Can Trust
HIPAA-compliant data pipelines, unified patient records, and clinical dashboards built for healthcare organizations that cannot afford data they do not trust. From fragmented EHR systems to a single source of truth.
The Problem
Healthcare Data Challenges We See Every Week
HIPAA Compliance Gaps
Data moving between systems without proper encryption, access controls bolted on as an afterthought, and audit logs that do not capture what regulators actually ask for. One finding can cost millions.
Fragmented EHR/EMR Systems
Epic in one facility, Cerner in another, a custom system from 2009 in the third. No unified patient view. Clinicians making decisions with incomplete records because the data lives in silos that do not talk to each other.
Claims Processing Delays
Mainframe batch jobs running overnight, 14-day adjudication averages, and providers threatening to leave your network because they wait too long to get paid. The data is there but the pipeline cannot keep up.
Siloed Patient Data
Patient information scattered across registration, billing, clinical, and pharmacy systems. Researchers wait 6 weeks for de-identified datasets. Care coordination suffers because nobody has the full picture.
Legacy Reporting Infrastructure
Crystal Reports from 2012. Excel workbooks emailed monthly. Dashboards that take 4 hours to refresh. Leadership making decisions on data that is two weeks old because the reporting stack cannot do better.
How We Help
Healthcare Data Engineering That Ships
Snowflake Health Data Lakehouse
A single, governed platform for clinical, claims, and operational data. Built on Snowflake with network isolation via Azure PrivateLink, tag-based PII masking, and role-based access that satisfies HIPAA auditors. Your data stays secure and your teams get the access they actually need.
Azure Data Factory ETL for Claims
Automated claims processing pipelines that replace mainframe batch jobs. We build ADF pipelines that ingest claims data from legacy systems, validate against business rules, and load into Snowflake for real-time adjudication tracking. No more 14-day waits.
HIPAA-Compliant Data Governance
Automated PII detection, dynamic data masking, audit logging on every query, and tag-based access policies. Compliance is not a checkbox we fill at the end. It is built into every layer of the pipeline from ingestion to dashboard.
Power BI Clinical Dashboards
Dashboards for clinical operations, claims queues, patient outcomes, and financial performance. Row-level security so each department sees only their data. Refreshed in minutes, not hours. Built with input from the people who will actually use them.
Real-Time CDC for Patient Records
Change data capture pipelines that sync patient records across systems in near-real-time. When a clinician updates a record in one EMR, the unified view reflects it within minutes. No more stale data driving clinical decisions.
Proof It Works
Healthcare Projects With Real Numbers
Healthcare Insurance Company — Claims Processing Overhaul
A healthcare insurance company with 2,400 employees was processing 180K claims per month through a mainframe batch system. Average adjudication time was 14 days. Providers were threatening to drop the network. We built Azure Data Factory pipelines to replace the legacy batch processing, loaded everything into Snowflake, added dbt transformation layers for business rule validation, and deployed Power BI dashboards for real-time queue visibility.
Multi-Location Healthcare Provider — Data Governance & HIPAA Compliance
A 3,000+ employee healthcare provider had 8 EMR systems and zero unified view. HIPAA auditors had flagged access control gaps. Researchers waited 6 weeks for de-identified datasets. We deployed Snowflake behind Azure PrivateLink, built automated PII masking with tag-based policies, and enabled secure data sharing for research teams.
Our Stack
Healthcare Data Technology
Healthcare Data Questions
We Hear Every Week
We build HIPAA compliance into every layer of the data pipeline. That means encryption at rest and in transit, role-based access controls, automated PII detection and masking using tag-based policies, audit logging on every data access event, and network isolation through Azure PrivateLink or AWS PrivateLink. We do not bolt compliance on at the end - it is the foundation of the architecture.
Yes. We have unified data from Epic, Cerner, Allscripts, and custom EMR systems into a single Snowflake health data lakehouse. We use FHIR R4 and HL7 v2 standards for interoperability, build CDC pipelines for real-time patient record updates, and handle the schema differences between systems so your clinical and operational teams get one consistent view.
Most healthcare data platform projects take 10 to 16 weeks depending on the number of source systems and compliance requirements. A focused claims processing pipeline might take 8 to 11 weeks. A full multi-EMR unification with governance and clinical dashboards is closer to 14 to 18 weeks. We run discovery in week one so you get a realistic timeline before any commitment.
We run both systems in parallel during migration. Your existing reports keep working while we build and validate the new platform. We do row-count reconciliation, data quality checks, and side-by-side comparison before cutting over. No one loses access to their reports, and we do not flip the switch until the new system matches or exceeds the old one in accuracy and performance.
Ready to Modernize Your Healthcare Data?
Tell us about your EHR systems, compliance requirements, and what is not working. We will map out a realistic plan with timelines and costs.
Schedule a Healthcare Data Assessment