Healthcare data is complex by design. Your infrastructure should not be.

Healthcare technology companies generate and manage some of the most complex data in any industry. Claims data structures with dozens of entity relationships. Billing systems that evolved over decades. Regulatory reporting requirements that change annually. Multi-payer ecosystems where accuracy is not optional because financial and patient outcomes depend on it.

Most health tech companies we work with have outgrown their initial data setup. What started as a few SQL queries against a production database has become a tangle of pipelines that break on schema changes, reports that take hours to run, and a BI layer that nobody trusts.

Assessment-first data platforms. Every engagement starts with a strategic assessment: what systems exist, where data breaks, and what the business actually needs. That assessment becomes the foundation for a governed data platform, not a vendor pitch for tools you may not need.

Reporting automation that meets deadlines. At Blitz Medical Billing, month-end reporting took 8 hours per customer. CorrDyn automated the entire pipeline. The same reports now run in 30 minutes for all customers combined. For a home care platform, we rebuilt data infrastructure to meet a hard government reporting deadline, standardizing hundreds of raw SQL queries into governed models.

Cost-effective platform migrations. Health tech companies routinely overspend on data infrastructure relative to their actual query volumes and data sizes. We profile real usage patterns and migrate to platforms that match, cutting costs without cutting capabilities.

Embedded analytics for healthcare products. If your product needs to surface data to customers, partners, or internal stakeholders, we build the analytics layer that integrates directly into your application, with HIPAA-appropriate access controls throughout.

From our podcasts: [Reducing Dropout Rates in Clinical Trials with Miguel Cacho Soblechero](/podcasts/data-in-biotech/ep-04-miguel-cacho-soblechero-clinical-trials), and [Overcoming Data Fragmentation in Healthcare with Vera Mucaj](/podcasts/data-in-biotech/ep-09-vera-mucaj-data-fragmentation).

We understand the constraints. Regulated data environments, fixed reporting deadlines, complex multi-payer data structures, and teams that cannot afford downtime. We have seen the same billing data challenges, the same government reporting crunch, and the same "we need a data team but cannot hire one" problem across enough health tech companies to know what works and what wastes time.