We build HIPAA-compliant digital health platforms that improve patient outcomes, streamline clinical workflows, and bridge the gap between healthcare providers and the patients they serve, all engineered to the regulatory standards healthcare demands.
Healthcare technology fails when it ignores the unique constraints of clinical environments. We understand these challenges because we have solved them.
Healthcare software must comply with HIPAA, HL7, FHIR, and in some markets ISO 13485 and FDA 21 CFR Part 11. Non-compliance results in substantial penalties and patient trust loss. Most development teams are not equipped to navigate these simultaneously.
Most healthcare organizations operate on legacy EHR systems (Epic, Cerner, Meditech) that were not designed for modern API-based integrations. Connecting new digital health tools to these systems requires deep understanding of HL7 v2, FHIR R4, and proprietary API schemas.
Healthcare providers abandon digital tools that disrupt established clinical workflows, regardless of technical quality. Technology must fit into how clinicians actually work, not how engineers assume they work.
Healthcare data is among the most sensitive and most targeted by attackers. PHI (Protected Health Information) breaches carry regulatory penalties up to $1.9M per violation category plus reputational damage that is nearly impossible to recover from.
Patient data is fragmented across hospitals, labs, pharmacies, insurers, and wearables. Building systems that aggregate and harmonize this data while maintaining patient consent and data lineage is a significant technical challenge.
AI-powered diagnostic tools require clinical validation, bias testing across demographic groups, and explainable outputs that clinicians can interpret and override. Deploying AI in healthcare without these safeguards creates legal and patient safety risks.
Purpose-built technology designed around the clinical, operational, and regulatory realities of modern healthcare.
End-to-end virtual care platforms with HIPAA-compliant video consultations, patient scheduling, prescription management, and EHR integration. Built to support async and synchronous care models across web and mobile.
Custom electronic health record systems and integration layers connecting disparate clinical systems via HL7 v2, HL7 FHIR R4, and proprietary EHR APIs (Epic SMART on FHIR, Cerner Open Developer). Full PHI encryption at rest and in transit.
Computer vision models for medical imaging (radiology, pathology, dermatology), NLP-powered clinical note processing, predictive models for readmission risk and disease progression, with full explainability and clinical validation frameworks.
Software as a Medical Device development following IEC 62304, ISO 13485, and FDA 510(k) requirements. We develop embedded software, companion apps, and cloud backends for connected medical devices, with full audit trails and risk management documentation.
HIPAA-compliant data warehouses, population health dashboards, clinical analytics platforms, and real-world evidence systems that transform fragmented healthcare data into actionable clinical and operational intelligence.
Mobile and web applications for appointment management, medication adherence, chronic disease management, mental health support, and patient-provider communication. Built with accessibility (WCAG AA) and multilingual support for diverse patient populations.
Real systems built for real clinical environments. Each project below reflects our understanding of HIPAA compliance, EHR integration, and AI applications in regulated medical contexts.
Challenge: A hospital network needed a HIPAA-compliant digital-first consultation system that integrated with their existing Epic EHR without disrupting live clinical workflows.
What We Built: End-to-end telemedicine platform with WebRTC video consultations, automated prescription management, bi-directional EHR sync via HL7 FHIR R4, and patient scheduling that reduced no-show rates through automated reminders.
Challenge: A diagnostic imaging network with high radiologist caseloads needed AI assistance to detect pathologies faster and reduce reporting turnaround times without introducing clinical risk.
What We Built: Computer vision model trained on 50,000+ annotated DICOM images detecting 15 pathology categories. SHAP-based explainability heat maps overlay on images, confidence scoring visible to radiologists, and FHIR-compliant findings sync to EHR workstations.
Every component selected for security, compliance, and clinical-grade reliability.
Share your requirements and we will provide technical guidance, compliance recommendations, and a clear project timeline within 24 hours.