Science-first. Clinically validated.
HaloScape partners with academic institutions, hospitals, and technology leaders across three continents to develop and validate multimodal clinical AI through prospective research.
Our research is guided by a multidisciplinary Scientific Advisory Council — physicians, clinical researchers, and domain experts spanning cardiology, radiology, psychiatry, reproductive medicine, and sports science.
Six models. One decision support platform.
HaloSight integrates proprietary AI models into a unified clinical decision support system — combining continuous wearable biometrics with medical imaging analysis to surface clinically actionable findings at the point of care.
Multi-class 12-lead ECG classification spanning conduction abnormalities, structural changes, and ischemic patterns — screening for conditions that are frequently subclinical at presentation.
Pattern recognition across pulmonary, cardiac, and mediastinal domains in standard chest radiographs — trained on reference datasets to flag findings that warrant further clinical evaluation.
Patient-profile-to-publication matching engine that surfaces relevant peer-reviewed evidence from indexed literature based on clinical context.
Multi-drug interaction screening and safety signal analysis across patient medication profiles, with food-drug and dose-response considerations.
Accelerated lumbar MRI segmentation and grading for disc herniation — reducing radiologist reporting burden through automated preliminary assessment.
On-premise reasoning agent that synthesizes wearable data streams, imaging findings, and electronic health records into a unified clinical narrative.
From hypothesis to clinical evidence.
Clinical insight doesn't come from a single signal — it emerges where fragmented data converges.
Each research track unifies signals from wearables, imaging, and clinical records to generate insights that no single data source could reveal alone.
Collaborating with leaders across three continents.
Built for clinical-grade trust.
Information security management — systematic protection of sensitive health data through risk assessment, access controls, and continuous security monitoring across all operations.
Privacy information management extension to ISO 27001 — establishing controls for personally identifiable information processing, supporting both GDPR and HIPAA compliance frameworks.
AI management systems standard — governance framework for responsible development, deployment, and monitoring of artificial intelligence systems in clinical and health applications.
Software process improvement and capability determination — Level 2 achieved for managed processes, targeting Level 3 for established, standardized development practices organization-wide.
Full U.S. health data protection compliance with established Business Associate Agreements and infrastructure engineered for protected health information handling.
EU data protection regulation compliance — lawful basis determination, data minimization, purpose limitation, and cross-border transfer safeguards for European citizen health data.
Advancing clinical evidence through partnership.
We welcome inquiry from academic institutions, clinical research organizations, and health technology innovators whose work intersects with multimodal clinical AI, wearable-derived digital biomarkers, or clinical decision support systems.
Propose a collaboration→