NeuralCare AI deploys deep learning across patient data streams to surface early disease signals — up to 48 months before conventional diagnosis.
Healthcare generates more data than any other industry — yet 70% of it goes unanalyzed. The cost is measured in lives.
Over 60% of cancers and chronic disease cases are diagnosed at Stage III or IV — when treatment costs 8× more and outcomes are dramatically worse.
A single patient generates 80MB of data per year. Clinicians review less than 1% of it. Critical early signals — in labs, imaging, and vitals — go undetected.
Physicians toggle between 11+ systems per shift. Cognitive overload drives 40% diagnostic error rates for complex presentations — even in top-tier centers.
Our transformer architecture ingests longitudinal EHR data, imaging biomarkers, genomics, and real-time vitals to compute dynamic disease risk trajectories — updated on every new data point.
NeuralCare's federated architecture keeps patient data within your perimeter. Only encrypted gradient updates traverse the network — enabling model training at population scale while maintaining full HIPAA, GDPR, and NHS IG compliance.
NeuralCare embeds directly into Epic, Cerner, and Oracle Health workflows. Risk scores, recommended actions, and evidence citations surface as contextual sidebars — no new logins, no context switching.
Continuous FHIR-native streams from EHR, imaging, lab, genomics, and wearable sources — structured and unstructured.
Transformer models run GPU-accelerated inference via ONNX Runtime and TensorRT — sub-50ms for real-time clinical alerts.
Dynamic risk scores with explainable attribution — every flag linked to contributing biomarkers and evidence-based clinical guidelines.
Alerts and recommended care pathways delivered inside Epic, Cerner, and via HL7 — driving measurable patient outcomes.
Clinical-domain BERT and GPT variants pre-trained on 500M de-identified patient records, fine-tuned per disease category with LoRA adapters for efficient deployment.
TensorRT-optimized model serving on A100/H100 clusters delivers sub-50ms inference at scale — 4.2M+ inferences per hour per deployment cluster.
Decentralized model training with differential privacy across 340+ hospital nodes — no patient data ever leaves the facility perimeter.
Automated CSRD, GRI, and FDA 21 CFR Part 11 compliance reporting. Built-in audit trails, model cards, and explainability documentation for regulatory submissions.
NeuralCare flagged a patient for early-stage cardiac dysfunction 14 months before our standard screening protocol would have caught it. That kind of lead time changes everything in treatment outcomes.
The federated learning model meant we could participate in network training without ever exposing patient data. It was the only AI vendor that our information governance team approved on first review.
Sub-50ms inference in our Epic workflow means clinicians never wait for insights. It's as fast as looking at a lab value — but it synthesizes 3 years of patient history in that same moment.
Transparent pricing for every stage of your AI health journey. View full pricing →
Full platform access for pilot programs and proof-of-concept deployments.
Unlimited scale with dedicated infrastructure, full model suite, and SLA guarantees.
Academic institutions, health system research divisions, and pharma R&D teams.
Join 340+ health systems using NeuralCare AI to detect disease earlier, improve outcomes, and reduce the cost of care.