AUTOFLUORESCENCE IMAGING • VIRTUAL H&E • AI MARGIN INTELLIGENCE

Pathology at
surgical speed.

SwiftDx turns fresh surgical tissue into a pathologist-familiar H&E slide and an AI margin report — without a cryostat, a stain, or a wait. From excision to readout in under five minutes.

MVP VALIDATION

Live Diagnostic Metrics

94–97%

H&E Concordance

72h → 5m

Turnaround Reduction

$3,000

Saved per Case

96%

Gross Margin at Scale

THE PROBLEM

Surgeons operate blind
on tumour margins.

Standard pathology turnaround runs 24–72 hours. SwiftDx targets under 5 minutes, right at the bedside.

1 in 5

Patients face repeat surgery

Positive margins missed intraoperatively drive re-excision — extra trauma, extra cost, extra time under anaesthesia.

65–90%

Hospitals lack intraoperative access

Most hospitals worldwide have no intraoperative pathology capability at all — no specialist on call, no equipment on hand.

24–72h

Standard turnaround

Traditional histopathology requires fixation, sectioning, staining, and manual review before a margin can be verified.

$15–40k+

No specialist, no cryostat

Histopathologist expertise and cryostat lab infrastructure are simply unavailable in most operating environments.

HOW SWIFTDX WORKS

Tissue in.
Insight out.

We turn a three-day lab process into a five-minute bedside workflow — eliminating physical sectioning and staining with autofluorescence imaging, virtual staining, and AI-assisted analysis.

01
Collection

Optical sectioning of fresh tissue

The surgeon provides a fresh tissue specimen immediately after excision — no fixation, no chemical prep required.

Fresh surgical tissue specimen
02
Imaging

AutofluoroSense imaging

The tissue is illuminated inside a dark chamber under 280nm UV excitation. Surface fluorescence creates a virtual optical section roughly 2–3 μm deep.

Optical sectioning setup
03
Virtual Staining

Virtual H&E generation

A Pix2Pix / U-Net model converts the raw fluorescence capture into a pathologist-familiar H&E representation — no chemical staining required.

Autofluorescent raw output Raw capture
Virtual H&E overlay AI generated
Virtual H&E overlay large
04
AI Analysis

Margin intelligence analysis

A MONAI ResUnit + vision-language head analyses tissue morphology and flags suspicious regions with a confidence-scored margin report.

Live Readout SDX-042
TissueBreast Margin
Margin StatusPOSITIVE
Tumor Distance0.4 mm
Confidence96.2%
RecommendationRe-excise
05
Clinical Output

Pathologist review

The generated slide and margin report are reviewed by a pathologist, who remains the final clinical decision maker — validated against the gold-standard H&E slide.

Actual gold standard H&E slide

Optical Depth

2–3 μm

Virtual section depth from surface fluorescence.

Exposure

3s

Per-capture imaging exposure time.

Sectioning

0 cuts

No microtome or physical sectioning required.

Output

AI Report

Structured margin report ready for sign-off.

VALIDATION

Already outperforming
frozen section.

Results derived from internal testing and limited-scale comparative studies — not yet clinically validated.

SwiftDx MVP · Current Dataset
94–97%

H&E CONCORDANCE

  • Sensitivity 0.96
  • Specificity 0.91
Frozen Section · Standard of Care
0.81

SENSITIVITY

  • Re-operation rate 20–40%
  • PLOS ONE meta-analysis · 6,769 cases

Virtual Staining

Pix2Pix / U-Net

31.4M parameters · 180ms per patch · SSIM 0.90–0.92.

Margin Classifier

MONAI + VL Head

86M parameters · MONAI ResUnit backbone · >90% precision.

Clinical Output

Structured Report

Margin label, confidence, evidence patches, heatmap, HL7/FHIR JSON.

Regulatory

MDA / FDA SaMD

Audit logs and locked validation built in from the start.

MARKET & BUSINESS MODEL

A $5.75B market,
50× cheaper to deploy.

Digital pathology market

$1.3B 2025 $5.75B 2034

Growing roughly 3× in a decade at a ~17% CAGR, driven by AI, cloud imaging, and rising cancer burden. Total addressable market: $36.7B. SwiftDx 5-year target: $130M.

The ask

$225K Clinical Validation Round · 2026

41% Regulatory · 28% Clinical Pilots · 21% Hardware & Ops · 10% Data Annotation & Model Improvement.

SwiftDx
Frozen Section
Setup Cost
~$400
$15,000–$40,000+
Per-Case Cost
~$30
$150–$500
STRATEGIC PARTNERSHIPS

Pan-continental
from day one.

Six partner organisations already on board across network access, hospital pilots, and research.

Commonwealth Medical Association · 54 nations
National Cancer Society Malaysia
HCG Cancer Centre, Bengaluru
Sundaram Arulraj Hospitals
Hospital Umra, Malaysia
Spartan Health Sciences University
TeleCure
TEAM & ADVISORS

Clinical, technical,
and regulatory expertise.

Amay Kashyap

Amay Kashyap

Healthcare AI

Mukund MV

Mukund MV

AI Engineering

Dr. Yin

Dr. Yin

Epidemiology & AI

Dr. Duane

Dr. Duane

Clinical Adoption

Isabel

Isabel

Legal & Regulatory

Yun Yin

Yun Yin

Biology

Tan Sri Dr. Noor Hisham Abdullah

Dr. Noor Hisham Abdullah

Advisor · Public Health

Dato Peter Ng

Dato Peter Ng

Advisor · UCSI Group

THE FUTURE OF SURGICAL PATHOLOGY

Real-time pathology
for precision surgery.

SwiftDx combines virtual staining, digital pathology, reinforcement learning, and AI-assisted tumour analysis into a single surgical intelligence platform.