Radiant Network
Prototype · Investor Demo Ready

The AI-native operating layer
for modern radiology networks

Workforce orchestration, multi-state licensing intelligence, and AI-assisted clinical workflow — unified into a single operational layer so radiology networks can scale without fragmentation.

Request a Shadow Run radiantnetwork@proton.me
<8 min
STAT turnaround
98.2%
First-pass claim rate
40+
IMLC states covered
14 sec
Auto-coding time
Platform

Three pillars. One operational layer.

The pieces that make radiology networks work — orchestration, compliance, and clinical AI — finally connected in real time.

Workforce Orchestration
Right radiologist. Right study. Right now.
Real-time routing across your credentialed radiologist network — filtered by state license, subspecialty, malpractice status, and live workload. STAT studies are never manually assigned.
  • Multi-state IMLC routing
  • Subspecialty matching
  • Workload balancing
  • Credentialing status checks
Licensing Intelligence
Coverage gaps caught before they become compliance gaps.
Continuous monitoring of multi-state license status, renewal timelines, and malpractice coverage across your entire radiologist network. What-if modeling shows exposure before it becomes a problem.
  • IMLC compact tracking
  • Renewal alert system
  • Coverage risk scoring
  • What-if scenario modeling
AI-Assisted Workflow
Decision support, not autonomous diagnosis.
Claude Vision provides radiologists with pattern recognition and structured findings as a consultation layer — not a replacement. Auto-coding and claim submission complete the loop from read to reimbursement.
  • Claude Vision decision support
  • AI-radiologist consensus workflow
  • Auto CPT / ICD-10 coding
  • Claim submission & tracking
Why now

The problem is fragmentation.
We are the connective layer.

The Problem
STAT studies wait for manual radiologist assignment
License lapses go undetected until a claim is denied
Diagnostic AI flags sit in dashboards — no operational follow-through
Billing coding is manual, slow, and error-prone
Our Position
Rad AI, Aidoc, Viz.ai
Detecting findings in images
RIS / PACS vendors
Study storage and basic workflow
Credentialing software
Static license management
Radiant Network
Operational intelligence connecting all of it
We are not competing with diagnostic AI companies — we are the operational layer that makes all of them more useful.
Integration

Your existing diagnostic AI
investment doesn't go to waste.

Radiant Network imports findings from Rad AI, Aidoc, Viz.ai, and other vendors via DICOM SR and HL7 FHIR. Their finding becomes our trigger.

Third-Party AI Integration DICOM SR · HL7 FHIR
Diagnostic AI
Rad AI · Aidoc · Viz.ai
›
DICOM SR Import
HL7 FHIR · structured
›
Radiant Routing
IMLC · subspecialty
›
Physician Sign-Off
Review · consensus
›
Claim Filed
CPT · ICD-10 · payer
Rad AI
Triage & prioritization
Aidoc
Clinical AI platform
Viz.ai
Care coordination AI
"Without Radiant Network, a Rad AI triage flag sits in a dashboard. With it, that flag triggers credentialed routing, escalation, physician sign-off, and a filed claim — automatically."
Status

Where we are.

Stage
Prototype
Investor demo ready
Next Step
Shadow Run
Real data · no patient impact
Goal
Series Seed
Network + data access

This prototype demonstrates the full pipeline — intake to claim — with real AI (Claude Sonnet) and simulated DICOM data. The shadow run phase connects to real hospital data in read-only mode: validating routing logic, license checks, and coding accuracy without touching clinical workflow.

Ready to see this with your data?

We're onboarding shadow run partners now — read-only access to your workflow data, no patient impact, full validation of routing logic, license compliance, and billing accuracy before you commit to anything.

Request a Shadow Run Get in Touch
Sam Brooker  ·  radiantnetwork@proton.me  ·  radiantnetwork.ai