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AI-Powered Radiology ⚡ POWERED BY NVIDIA

Instant Diagnostic Clarity. Accelerated by NVIDIA H100.

Veltneon builds local GPU-accelerated radiology pipelines that parse X-rays and detect abnormalities instantly.

Currently in private beta testing across select health systems, preparing clinicians for rapid evaluation, high sensitivity detection, and Epic/Cerner EHR chart integration.

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Technology Partner: NVIDIA Inception Member (GPU-accelerated healthcare pipeline)
Auravita AI Radiology Platform Analyzing Chest X-Ray

Auravita™ In-Clinic Dashboard

STATUS: INFERENCE_ACTIVE [96.4% CONFIDENCE]

Inference Pipeline

How Auravita Scans and Integrates

A secure, de-identified radiology routing pipeline powered by local H100 GPUs and EHR writeback connectors.

PACS Router DICOM Ingestion PHI Sanitizer Demographics Scrub NVIDIA H100 TensorRT NIM Inference Engine EHR Writeback FHIR Integration
Launch Announcement

Countdown to Public Launch

Our beta testing completes soon. Auravita officially launches for clinical integration on September 16, 2026. Watch our progress live:

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About Veltneon

Clinical-Modern Diagnostic Intelligence

Veltneon Inc. is a seed-stage medical technology company developing dedicated, hardware-isolated, GPU-accelerated AI systems that optimize radiology workflows. We deploy physical computing matrices directly inside hospital server layers, giving clinical teams instant diagnostic validation without exposing patient PHI to external networks.

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The Paradigm

Breaking the Diagnostic Bottleneck

Analyzing radiological images requires low-latency architectures that secure patient data boundaries.

The Clinical Problem

Radiologist Burnout & Delay

Emergency centers face severe backlogs of unread X-rays. Crucial trauma scans (such as hairline fractures or pulmonary collapses) wait hours in queue, increasing emergency read bottleneck issues.

X-RAY_QUEUE: 142 Pending DELAY: 4.2 Hours
The Architecture Bottleneck

Cloud Latency & Privacy Risks

Routing full-resolution DICOM files to public cloud APIs introduces network latency and privacy complications. Stripping PHI and maintaining HIPAA validation on shared virtual networks is complex.

PUBLIC_CLOUD_ROUTING LATENCY SPIKE
Veltneon's Solution

local H100 Hardware Stack

Veltneon deploys dedicated NVIDIA H100 arrays locally within hospital subnets. DICOM files are ingested, stripped of PHI inside secure local buffers, evaluated in under 300ms, and written back to EHR.

Local H100 NIM Node SUB-300MS INFERENCE
Workflow Comparison

Operational Transition

A direct audit comparing legacy diagnostic workflows with Veltneon’s integrated GPU pipeline.

✕ Legacy Cloud & Manual Workflows

  • 01 Patient files routed over shared public internet nodes, increasing data transit overhead.
  • 02 Patient identifiers (name, DOB) embedded in DICOM headers, creating privacy risks.
  • 03 Long queue times (average 2.4s) due to cloud network overhead and database lags.
  • 04 Clinicians manually write or copy-paste diagnostics summaries into hospital charts.
  • 05 Worklists sorted chronologically, delaying critical trauma reads.
  • 06 Dependence on public servers, creating risks of offline bottlenecks during outages.

✓ Veltneon’s Dedicated Stack

  • 01 Scan routing is completely isolated within the local hospital subnet.
  • 02 Zero-knowledge filter strips PHI at source before entering the AI core.
  • 03 Dedicated NVIDIA H100 cores deliver sub-300ms inference times.
  • 04 Automatically compiles and writebacks validated findings as FHIR resources.
  • 05 WorklistPriority automatically promotes acute conditions to the top of queues.
  • 06 Local containers continue running offline even if the external hospital network drops.
Performance Indicators

Validated Sensitivity & Computational Speed

Veltneon evaluates system capability using simulated datasets and clinical sandbox runs. These metrics represent our benchmark targets for early health system pilots:

Classification Sensitivity Target 99.2%
In-Subnet Ingestion Latency 84ms
Zero-Knowledge PHI Scrubbing Success 100.0%
Cumulative X-Rays Analyzed (Beta Sandbox)
1,248,590+

Scans successfully audited across local testing clusters with zero safety exceptions.

Specialized Infrastructure

High-Performance Features

Our platform includes modular nodes built specifically for hospital server deployment.

PACS-Link Node

Accepts raw DICOM scans directly from the imaging system. Caches data within a local isolated subnet to optimize read speeds.

Zero-Knowledge Filter

Strips all Protected Health Information (PHI) metadata tags from the files before routing to model registers, ensuring compliance.

TensorRT Optimization

Model weight layers are serialized and optimized using NVIDIA TensorRT, maximizing H100 hardware core throughput.

H100 Hardware Compute

Parallel matrix multiplication calculations are executed locally on dedicated H100 hardware units to bypass legacy queues.

WorklistPriority Triage

Promotes critical trauma findings (like collapses or bleeding) to the top of PACS worklists automatically to reduce clinician delays.

FHIR API Writeback

Translates diagnostic segmentations into FHIR-compliant payloads, writing results directly back to Epic/Cerner charts.

"Instant Radiology Intelligence. Secured Inside Your Hospital Subnet."

Veltneon accelerates diagnostic throughput while maintaining zero-knowledge patient data privacy.

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