One public portal for healthcare data quality, visualization, categorization, and operating proof.
Health Data In Motion Platform brings together Data Motion Platform, DQM / Data Quality Monitor, and Atlas Nexus for broad implementation work across data quality, data visualization, data categorization, research, public health, and operator-safe evidence.
Live system walkthrough
Review the running clinical experience, care-gap workflows, and role-based views before a buying conversation.
Validation dashboard
Inspect the test, architecture, and control evidence that backs the implementation story.
Evidence room
See packaged buyer-facing evidence for architecture, implementation, and release-grade diligence.
Architecture review
Understand the deployment boundary, event-driven pipeline, and data-control posture without reading source code first.
Start here to find the Health Data In Motion solution you need.
The umbrella site explains how the product family fits together across data quality, visualization, categorization, research, public health, and implementation proof. Each product page then gives a direct login path, evidence links, and access expectations.
Solution directory
Data Motion Platform
Move approved healthcare events, quality workflows, evidence packets, and integration handoffs through a customer-controlled operating boundary.
DQM / Data Quality Monitor
Score source readiness, conformance, completeness, and data-quality gates before clinical, regional, or analytics workflows depend on them.
Atlas Nexus
Coordinate operator-safe evidence, readiness state, rollout decisions, and regional intelligence without making the cloud tier the PHI-resident execution system.
Broad implementation across the data lifecycle.
Health Data In Motion is not only a data-movement story. It is a practical implementation model for turning raw clinical and operational feeds into trusted, categorized, reviewable information for care, research, public health, and executive decision support.
Data quality
Profile source readiness, measure completeness, conformance, remediation state, and trust signals before downstream work depends on the data.
Data visualization
Give operators and reviewers role-based views of quality signals, care gaps, rollout status, and evidence without exposing raw payloads publicly.
Data categorization
Classify cohorts, source findings, artifacts, implementation states, and review priorities for research, public health, and operational follow-through.
Research and public health
Support safe cohort review, regional program coordination, implementation proof, and public-health readiness with clear authority boundaries.
The buyer problem is not just analytics. It is deployment confidence.
Quality programs already know the pain. The harder part is finding a path that improves responsiveness without forcing another opaque platform decision.
Quality work arrives too late
Clinical and quality teams often see gaps after manual exports, spreadsheet joins, and delayed scorecards have already slowed action.
Deployment risk blocks progress
Buyers do not want another opaque black box, another forced migration, or another long implementation that hides real operating evidence.
Proof is hard to evaluate
Enterprise reviewers need to see what is live, what is validated, and what controls exist before they commit time or money.
A lower-risk path from proof to deployment.
Data Motion Platform is positioned for organizations that want real-time quality measurement and data movement without surrendering deployment control. The product story stays tied to an implementation story you can actually inspect.
- ✓Keep PHI and operational control within your infrastructure boundary.
- ✓Connect existing FHIR, HL7 v2, and bulk-data sources without replacing current systems.
- ✓Run quality logic in near real time instead of waiting for manual reporting cycles.
- ✓Turn categorized data and safe visual summaries into research, public-health, and operational review paths.
- ✓Give compliance and technical reviewers tangible proof, not just promises.
Evidence buyers can use internally
The first engagement should leave buyers with enough implementation signal to brief executives, technical leaders, and reviewers without hand-waving.
Every major claim on this site has a proof destination.
Buyers should be able to move from headline to proof without needing a custom explanation. These are the first-stop destinations for diligence.
Evidence Room
Buyer-facing proof packages, readiness materials, and curated review paths.
Validation
Architecture decisions, quality controls, and implementation evidence tied together.
Architecture
Deployment boundaries, event-driven flow, and system shape explained for evaluators.
The buyer story is anchored to real screenshots, role-based views, and validation artifacts rather than abstract marketing diagrams alone.
Start with a pilot. Expand after proof.
Buyers do not need to commit to the largest deployment path first. The site now reflects a staged motion: validate fit, confirm proof, then scale to the operating model you need.
Starter
Single-node Docker deployment for proof of concept
Professional
Clustered deployment with high availability
Enterprise
Kubernetes deployment for maximum scale
Hybrid Cloud
On-premise gateway with cloud compute
A guided path from first review to internal buy-in.
Review the operating proof
Start with the live demo, validation dashboard, and architecture evidence to confirm the system is real and reviewable.
Run a scoped walkthrough
Use a buyer-led walkthrough to map your environment, deployment boundary, and first proof-of-value motion.
Expand after evidence
Move from pilot to broader deployment only after the organization sees the operating model, controls, and implementation fit.
Questions buyers ask early
The first pass on the site should answer the basics, then hand buyers to proof surfaces and a walkthrough.
How long does deployment take?
Pilot deployment takes 2-3 weeks, Growth tier 4-8 weeks, and Enterprise 8-12 weeks. The timeline depends on your infrastructure readiness and integration complexity.
Do you support our EHR?
We support Epic, Cerner, Athena, and any FHIR R4-compliant server. If your EHR supports FHIR, we can integrate with it.
Can we customize the measures?
Yes! We include 52 HEDIS measures out of the box, and you can add unlimited custom measures using our CQL framework. Custom measures start at $3K-8K each.
Is our data secure and compliant?
Yes. We're HIPAA-compliant with multi-tenant isolation, HIPAA audit logging, TLS 1.3 encryption, and role-based access control. Data never leaves your FHIR server - we query it directly.
Book the walkthrough before you decide how far to go.
The fastest way to evaluate the platform is to review the live proof together: deployment posture, architecture, validation, and the operating experience in one session.