Who We Serve

Built for Healthcare Enterprises That Aggregate Data Across Organizations

Lynqsys serves organizations that can't afford to discover data quality issues months after ingestion:

The common challenge: You aggregate data from multiple organizations and need it refined, governed, and AI-ready: not raw and requiring endless downstream ETL.

Multi-hospital health systems with data integration needs

Unifying data across facilities and EHR systems for enterprise analytics
Acquired multiple hospitals? Now have data silos?
Every acquisition brings another EHR system, different terminologies, and duplicate patient records. Your enterprise data warehouse gets raw, inconsistent data that requires months of ETL before it's usable.
Lynqsys refines data at ingestion - creating unified patient records across facilities with identity integrity, semantic normalization, and quality controls built-in.
Result: Enterprise-ready data for analytics, population health, and AI without endless downstream cleanup.

Medicare Advantage and Medicaid managed care plans

Risk adjustment and encounter validation at scale with audit-ready processes
Struggling with encounter data quality and risk adjustment accuracy?
You're aggregating claims, clinical, and SDOH data from hundreds of network providers but inconsistent formats and quality issues undermine risk scores and create CMS compliance concerns.
Lynqsys refines data at ingestion - validating encounters, normalizing diagnoses, and maintaining provenance for audit-ready risk adjustment and quality reporting.
Result: Accurate RAF scores, defensible encounter submissions, and care management data you can trust.

Health Information Exchange Consuming Diverse Data Sources - visual selection.png

Health Information Exchanges (HIEs) and RHIOs

Processing data from hundreds of providers with real-time quality controls
See How a Major HIE Transformed Operations
Legacy HIE Platform Becoming a Barrier?
After 15-20 years, your platform moves data but can't support modern use cases: AI applications, real-time analytics, value-based care, state contracts requiring data quality guarantees.
Lynqsys was purpose-built for what technology can finally deliver: real-time data refinement at scale with transparency, governance, and AI-readiness built-in.
Enable capabilities that were impossible with legacy infrastructure—proven at 1M+ messages daily.

Accountable Care Organizations (ACOs)

Coordinating care with accurate attribution and longitudinal patient views
Spending months reconciling data from independent practices?
You're coordinating care across providers with different EHRs, but patient matching issues, incomplete records, and inconsistent quality measures undermine attribution and performance reporting.
Lynqsys refines data at ingestion - creating accurate patient attribution, longitudinal care records, and quality measures you can trust across your entire network.
Result: Confident risk stratification, accurate quality reporting, and care coordination based on complete patient views.

Healthcare AI and analytics companies

Pre-refined, validated datasets for model training without months of preparation
Spending 80% of your time preparing data instead of building models?
You're aggregating healthcare data from multiple sources to train AI models but inconsistent semantics, missing context, and identity issues mean months of cleanup before model development can even begin.
Lynqsys delivers pre-refined, AI-ready datasets - with identity validation, semantic normalization, longitudinal stability, and provenance tracking built-in.
Result: Focus on building breakthrough models, not endless data preparation.

Population health management organizations

Complete patient records with quality indicators for confident decision-making
Can't act on insights because you're not sure the data is complete?
You're managing populations across providers and care settings but fragmented records, care gaps you can't see, and uncertain data quality mean your interventions are reactive, not proactive.
Lynqsys creates complete longitudinal patient records with quality indicators by source and field. Know which patients need outreach and trust the data driving your decisions.
Result: Proactive care management, visible gaps, and interventions based on data you can defend.

Are You Facing These Challenges?

If you aggregate healthcare data across organizations, you're likely experiencing:

☐ Months-long ETL cycles for every new analytics project

☐ Data quality issues discovered too late to prevent problems

☐ Patient matching challenges creating duplicates and overlays

☐ Inconsistent formats from multiple source systems

☐ Analytics teams spending more time cleaning than analyzing

☐ Inability to confidently support AI or advanced use cases

You're not alone. HIEs, health systems, ACOs, payers, and healthcare AI companies all face these challenges when aggregating data across organizations.

Lynqsys addresses the root cause: Traditional platforms move data and leave refinement to downstream teams. We refine data at ingestion with identity validation, semantic normalization, and quality controls built-in.

The result? Organizations processing 1M+ messages daily with data that's immediately trustworthy and ready for analytics, AI, and regulatory reporting.