Three numbers decide whether your data platform is working. Audit-evidence assembly: weeks or minutes? Analyst data-prep time: 40% or under 10%? AI on internal data: production or proof-of-concept? NonStop fixes the math.
Schedule a 45-Minute Architecture Review →Most healthcare data infrastructure was built before WGS became routine, FHIR was a delivery requirement, or HHS OCR expanded enforcement.
HIPAA-compliant by architecture. Scoped to named outcomes: TAT, cost-per-sample, audit cycle, AI-readiness.
Every sector has distinct regulatory requirements, data formats, and infrastructure patterns. NonStop brings production experience across all five.
Every technology choice is deliberate. Selected for HIPAA-aligned architecture, clinical-grade reliability, and petabyte-scale genomic data processing.
Most engagements start with a 45-minute Architecture Review. We map your current state across the eight disciplines, identify the highest-ROI investment, and scope a phased plan with named outcomes.
"Stop maintaining the data infrastructure. Start running it as a platform. We will come back with a realistic scope, a phased timeline, and outcome targets you can take to your CFO."
Three reasons every Tier-1 ICP asks about. Here are the answers.
Knowing Spark is not knowing how multi-allelic variants split. Or why GRCh38 reference handling breaks naive normalization. Or what FHIR Genomics Reporting actually requires. Every NonStop healthcare data team includes engineers who have shipped production for clinical genomics or life sciences customers.
HIPAA, CAP/CLIA, SOC 2, GDPR, and 21 CFR Part 11 controls live in the IaC and the data platform — not in a slide deck. SOC 2 readiness comes from how the platform is built, not how it is documented. We engineer compliance in, not bolt it on after.
Hours and resources are inputs. TAT, cost-per-sample, query latency, audit cycle time, and AI-readiness are outputs. Every contract names the output and the measurement methodology. You take those targets to your CFO before we start.
Both. Most engagements scope to four to six disciplines. Some are full-platform builds for Series A/B precision medicine companies. Some are single-discipline rebuilds for established labs.A production-ready clinical bioinformatics pipeline must be reproducible across runs, scalable for clinical sample volumes, auditable for regulatory compliance, and integrated with clinical systems such as LIMS and reporting platforms.
Yes. Migrations to AWS HealthOmics, Databricks, or Snowflake with Iceberg are one of our most common engagements. Typical timeline: 4–9 months end-to-end with a 60–90-day parallel-run period.
Yes. We engineer platforms that satisfy HIPAA, CAP/CLIA, SOC 2 Type II, GDPR, and 21 CFR Part 11 simultaneously. Data residency, encryption, and access controls are handled at the architectural level, not as per-region overlays.
Through dynamic PHI masking and synthetic data generation. Developers and data scientists work with synthetic or masked datasets that preserve statistical properties while not exposing real PHI.
Yes. Several NonStop engagements run on cloud lakehouse architectures with sustained processing of population-scale cohorts. Scale is a function of architectural choices made early - Iceberg partitioning, Spark execution tuning, storage tiering, spot-instance optimization.
Tell us:
We will come back with a realistic scope, a phased timeline, and outcome targets you can take to your CFO.
