Risemont AI

Expert medicine,
made universal.

We build medical intelligence that brings subspecialty-level diagnosis, treatment planning, and clinical reasoning to every hospital — regardless of size, geography, or resources.

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Medical Intelligence
FDA Pathway · 2026
The Mission

The best medicine
should not depend on where you are born.

Almost half the world lacks meaningful access to diagnostic care. Even in wealthy health systems, subspecialty expertise is concentrated in a handful of academic medical centers, and patients elsewhere receive different medicine than the same condition would receive miles away.

Risemont AI exists to close that gap. We build AI that delivers subspecialist-grade diagnosis, treatment planning, and clinical reasoning to every clinician who reads a scan or reviews a case — anywhere in the world.

~4 billion
people lack meaningful access to diagnostics
Lancet Commission on Diagnostics, 2021
5%
of adults experience diagnostic errors each year in outpatient care
World Health Organization, 2019
6× gap
in radiologist workforce between high-income countries and much of the world
Comparative workforce data, WHO / RSNA
1.9M
neurons lost per minute during acute stroke
Saver JL, Stroke, 2006
"

The greatest opportunity in medical AI is not to replace the world's best specialists. It is to make their expertise available in every hospital, at every scan, for every patient.

Our Technology

A platform for
expert clinical reasoning.

Our AI does more than flag findings. It reasons about clinical context — combining imaging, patient history, and evidence-based protocols to support diagnosis, planning, and treatment decisions across specialties.

I

Augments, never replaces

Our systems assist clinicians — they do not make decisions. Every finding is a recommendation that a licensed physician confirms, modifies, or overrides. Authority stays with the human.

II

Workflow-native

Our software integrates with existing PACS, EHR, and clinical infrastructure via DICOM and HL7 standards. No new hardware, no disruption to established workflows.

III

Explainable by design

Every output includes visual reasoning — spatial heatmaps, confidence intervals, and the anatomical or clinical logic behind each recommendation. No black-box decisions.

Platform Capabilities

Detection & Localization

Identification and spatial mapping of clinically significant findings across imaging modalities.

Clinical Reasoning

Integration of imaging, patient history, and guidelines to support diagnostic and treatment decisions.

Standards Integration

DICOM, HL7, and FHIR compliance for interoperability with existing hospital systems.

Regulatory-Grade Audit

Complete provenance and audit trails supporting FDA post-market surveillance and quality review.

Initial Programs

Two programs.
Ambitious in scope. Rigorous in execution.

Our initial programs demonstrate the platform across two of medicine's highest-impact domains — one where minutes decide outcome, the other where diagnostic precision determines the entire course of care.

Program 01

Neurovascular Imaging AI

First application · Intracranial hemorrhage detection on head CT

Intracranial hemorrhage is among the deadliest neurological emergencies. Detection speed determines survival and long-term function. Our AI reads non-contrast head CT scans in seconds, flagging candidate hemorrhages and prioritizing them in the radiologist's worklist.

Clinical Setting
Multi-site clinical partnerships across Southeast Asia, where radiologist shortages and stroke burden create the highest marginal impact.
Regulatory Path
FDA 510(k) submission targeted, with concurrent clinical validation supporting subsequent Asia-Pacific and EU regulatory pathways.
Program 02

Oncologic Pathology AI

Focus · AI-assisted analysis of tumor pathology

Cancer diagnosis and treatment planning depend on subspecialty pathology expertise that is scarce even in top-tier academic centers. Our AI supports pathologists in identifying, classifying, and characterizing tumors with subspecialist-grade precision.

Research Collaborations
Ongoing research collaborations with investigators at MD Anderson Cancer Center and Stanford University, building on established scientific relationships.
Strategic Rationale
Cancer pathology represents an area where AI can materially improve diagnostic quality and where the economics support broad deployment across care settings.

Additional programs in cardiovascular imaging, thoracic oncology, and multi-modal clinical reasoning are in preliminary evaluation.

Our Approach

Regulatory-first.
Clinically grounded.

Every Risemont AI program follows the same disciplined path from research through regulatory clearance to global deployment. The sequence protects patients, satisfies reviewers, and ultimately produces evidence that makes broad adoption possible.

Phase 01

Clinical Validation

Diverse multi-site partnerships

We partner with academic medical centers and community hospitals across geographies to validate model performance on the populations our products will serve. Partner clinicians are named investigators, ensuring FDA-grade study design.

Phase 02

FDA Submission

510(k) or De Novo pathway

With validated performance data, we prepare and submit our FDA application, selecting the appropriate cleared predicate device or novel classification pathway. Regulatory-grade documentation is built into our development process from day one.

Phase 03

Global Regulatory Expansion

Reference pathways worldwide

FDA clearance unlocks reference-based pathways in Japan (PMDA), Korea (MFDS), Singapore (HSA), the EU (CE marking under MDR), and additional jurisdictions. Regional adoption follows regulatory clarity and reimbursement structure.

Phase 04

Platform Expansion

Multi-program growth

Shared infrastructure — data pipelines, model architecture, regulatory frameworks, and clinical relationships — supports additional programs at lower marginal cost per indication. Each new program benefits from the platform built beneath it.

Leadership

Built by a team that has
shipped medical AI before.

HN
Portrait
Founder & Chief Executive

Hien Nguyen, Ph.D.

Medical AI engineer and researcher

Hien has spent thirteen years building AI systems that operate in safety-critical settings, from medical imaging to autonomous driving. His work spans the full arc from foundational research to products that function reliably at scale in clinical and operational environments.

He was a Research Scientist at Siemens Healthineers, where he contributed to early deep learning innovations in medical imaging that are now deployed globally across the Siemens diagnostic portfolio. He was also a Senior Scientist at Uber ATG, working on perception systems for autonomous vehicles. He holds a Ph.D. in Electrical and Computer Engineering from the University of Maryland.

13+ yrs
building medical AI, since 2013
Siemens
Healthineers — imaging AI research
Uber
ATG — perception systems
Maryland
Ph.D., Electrical and Computer Engineering
Scientific Advisors & Team

Risemont AI is supported by a growing network of scientific advisors including practicing radiologists, neurologists, and pathologists; regulatory affairs specialists with prior FDA submissions for AI/ML medical devices; and engineering hires scaling the platform across imaging modalities and clinical domains.

Contact

We welcome
serious conversations.

If you are an investor with medical AI experience, a health system leader considering a clinical partnership, a clinician-scientist interested in advisory roles, or a journalist seeking background, we would be glad to hear from you.

Direct Inquiries
hienvnguyen22@gmail.com
Hien Nguyen, Ph.D. · Founder
Operations
Headquarters — Houston, Texas
Clinical partnerships — United States and Southeast Asia

Please include your organization and the nature of your inquiry in your first message. We respond to all substantive outreach within five business days.