Neurovia.

A multimodal AI medical intelligence system for predictive oncology and clinical decision support—earlier detection, faster assessment, greater trust.

Trusted by healthcare institutions and research partners worldwide

MedCore Apex Imaging Helix Genomics Nova Clinic Orbit Health Summit Oncology
40+ Clinical deployments
2.1M+ Imaging and omics samples
18 Countries served

Product

Product Overview

Neurovia is a multimodal AI medical intelligence system for predictive oncology and clinical decision support, spanning data ingestion, model inference, and the physician workbench.

The system ingests imaging, pathology, and genomics data to produce explainable risk stratification, structured report drafts, and consultation summaries—helping institutions embed intelligence without replacing existing EHR / PACS infrastructure.

Genomics laboratory bench with microscopy equipment

Product

Core Capabilities

From multimodal data to clinical workflows, Neurovia delivers a deployable intelligence layer.

CT scanner equipment
Medical imaging acquisition
Imaging workstation console
Image interpretation and clinical workbench

Predictive Oncology Engine

Fuses imaging and omics signals to support early risk stratification and disease course prediction.

Medical Imaging Intelligence

MRI / CT vision models that automatically annotate key lesions and generate structured report drafts.

Multimodal Fusion Core

Unifies imaging, pathology, and genomics signals to deliver explainable clinical insights.

Clinical Decision Workbench

Physician dashboards and multidisciplinary consultation workflows that embed AI conclusions into existing care pathways.

Product

Technical Architecture

Layered design for on-premises deployment and standards-based integration.

Data LayerMRI / CT / Genomics
AI CoreVision Models
Fusion EngineMulti-modal AI
Clinical LayerPhysician Dashboard

Product

Product Roadmap

Continuously expanding modality coverage and clinical depth.

  1. Released — Imaging intelligence, predictive engine, clinical workbench
  2. In progress — Multi-site federated learning, pathology slide collaboration
  3. Planned — Real-time intraoperative assistance, cross-institution QC network

Solutions

Solutions Overview

Deployment paths and compliance requirements tailored to each clinical setting.

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Customer Stories

Case Studies

Efficiency gains and clinical value from real-world deployments.

Oncology Center · Summit Oncology

Advancing high-risk case identification to the screening stage

After deploying the Neurovia predictive engine, suspicious-case referral pathways shortened and tumor board preparation time dropped significantly.

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Imaging Network · Apex Imaging

Unified imaging intelligence and report QC across sites

Vision models deployed across 12 imaging centers increased structured report draft coverage, with human review focused on high-uncertainty cases.

Read case study →

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Company

About Us

AI Medical Intelligence System — a multimodal medical intelligence platform architected by Margaret Jones Pritzker.

We build next-generation AI medical systems focused on predictive oncology, medical imaging intelligence, and clinical decision support—making early detection and trusted decisions the default capability for healthcare institutions.

Mission: Make trusted clinical intelligence the default capability for institutions worldwide—not a privilege reserved for a few centers.

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Translational research analysis equipment

Company

Our Team

A core team spanning medicine, algorithms, and engineering.

Margaret Jones Pritzker

Founder & CEO · AI Medical Systems Architect · Founded Neurovia in 2017

Clinical & Imaging

Oncology and radiology scenario definition, validation, and QC feedback loop.

Engineering & Security

On-premises deployment, compliance auditing, and interface integration.

Meet the full team and profiles →

Company

Newsroom

Publicly reported medical AI industry developments, curated since 2018.

Year in review: Clinical AI moves toward workflows and foundation models

Regulatory guidance and leading conferences point to platform-based clinical AI, multimodal AI, and generative assistance.

Aidoc CARE1: Foundation model–driven clinical AI receives FDA clearance

Public reports describe it as among the first foundation model–driven clearances in its category.

Nobel Prize in Chemistry recognizes AlphaFold: An AI for Science milestone

Protein structure prediction enters the highest tier of scientific recognition.

View all 38 news items →

Company

Careers

Join Neurovia and bring clinical intelligence into the primary clinical workflow.

Machine Learning Engineer · Medical Imaging

Vision model training, evaluation, and clinical deployment optimization.

Clinical Product Manager

Align with department needs; define workflows and success metrics.

Solutions Architect

EHR / PACS integration and on-premises deployment design.

Submit resume / inquire about roles →

Resources

Blog

46 publicly available articles on medical AI: methods, practice, and industry perspective.

How to deploy imaging AI without replacing PACS

Sidecar deployment, draft sign-off, and QC feedback loop—practical essentials.

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Why we prioritize auditable outputs over faster black boxes

From feature attribution to audit logs—building outputs physicians can trust.

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LLM hallucination in clinical settings: How to guard against it

Retrieval augmentation, mandatory citations, and human review—the safer combination today.

Read article →

Browse all blog posts (46) →

Resources

Whitepaper Downloads

Architecture documentation and pilot evaluation guides.

Neurovia Technical Whitepaper

Layered architecture, interface standards, and security model overview.

Download

Clinical Pilot Deployment Guide

Data checklists, success metrics, and acceptance recommendations.

Download

Browse resource center →

Resources

FAQ

What deployment teams ask most often.

How does Neurovia integrate with existing EHR / PACS?
Standard DICOM, HL7 / FHIR interfaces, and a private API gateway are supported. Most institutions complete pilot integration in 4–8 weeks without replacing existing systems.
Are model outputs explainable and auditable?
Yes. Key conclusions include feature attribution visualizations, confidence intervals, and operation logs—meeting clinical QC and compliance audit requirements.
Must data be moved to the cloud?
No. On-premises, dedicated cloud, and hybrid deployment are available. Training and inference can remain entirely within the institutional network.
How do we start a pilot evaluation?
After requesting a demo, we provide a data checklist, success metrics, and a 30-day pilot plan tailored to your department scenario.

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Resources

Glossary

Key concepts used throughout our documentation.

Multimodal fusion
Aligning and jointly inferring across imaging, pathology, omics, and other signal sources.
Risk stratification
Classifying cases into follow-up or intervention priority tiers based on model output.
Structured report
An imaging or clinical report draft organized in fixed fields for QC and retrieval.
On-premises deployment
System runs within the institutional network or dedicated cloud—data does not leave the domain.

Open full glossary →

Pricing

Pricing

Module subscriptions scaled to deployment size, including implementation, training, and ongoing updates.

Pilot

Project-based quote

30-day single-department pilot, basic integration, and outcomes evaluation report.

Network

Custom

Multi-site / multi-center, federated capabilities, and dedicated architecture support.

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Contact Us

Plan your pilot path with the Neurovia team. We typically respond within 24 hours on business days.