AI Β· Pathology Β· Radiology

Catch Cancer
Before It Kills.

We build AI agents that analyze whole slide images and X-rays to detect cancer at Stage 0 β€” before symptoms appear. Upload a slide, get a precision heatmap in seconds.

Product Demo
The AI Pipeline

From Slide to Diagnosis in Seconds

Our AI agents run the full WSI diagnostic pipeline autonomously β€” from raw tissue segmentation to a clinical-grade heatmap showing cancer probability per region.

Raw whole slide image AI-generated cancer heatmap
Initializing AI Agents…
Next: Patch Extraction (Tiling)
Tissue Detection & Segmentation
Patch Extraction (Tiling)
Image Normalisation
Feature Extraction
MIL Model Inference
Heatmap Generation
The Problem

Cancer Kills Because It's Caught Too Late.

Pathologists and radiologists are overwhelmed by volume. Screening backlogs mean critical findings wait days for review. Manual analysis doesn't scale β€” and patients pay the price.

  • Late detection: Most cancers are diagnosed at Stage III or IV when survival rates collapse.
  • Burnout: Pathologists review hundreds of slides daily with no AI assistance.
  • Inconsistency: Inter-observer variability causes misdiagnoses that alter treatment paths.
  • Access: Rural and low-resource hospitals lack specialist radiologists entirely.
Our Solution

AI That Flags, Humans That Decide.

Our platform doesn't replace doctors β€” it arms them. Upload a whole slide image or X-ray, and our AI agents produce a cancer probability heatmap in seconds. Normal slides are triaged automatically. Suspicious ones are escalated with high priority.

Doctors see more patients. Labs process more slides. And cancers are caught at Stage 0, when they're still curable.

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What We Analyse

Multi-Modal Cancer Screening

One platform. Multiple imaging modalities. Every analysis produces an actionable, clinical-grade output.

Digital Pathology

Upload any whole slide image (WSI). Our MIL-based agents segment tissue, extract features, and generate a heatmap showing tumour regions and margins at sub-cellular resolution.

MVP Β· Live

Radiology Screening

Chest X-rays and CT scans screened for lung cancer, pneumonia, and fractures. Critical findings are flagged in real-time and prioritised for urgent radiologist review.

In Development

Mobile Screening

Phone-based screening for oral cavity cancer. Photograph the lesion β€” our model classifies it and recommends whether the patient should seek urgent care. No lab required.

Roadmap
How It Works

Three Steps. Zero Friction.

Designed to plug into existing hospital workflows with minimal integration effort.

01

Secure Upload

Send whole slide images or DICOM files via our API or web portal. HIPAA-compliant data handling throughout.

02

Agentic Analysis

AI agents run the full pipeline β€” segmentation, normalisation, feature extraction, and model inference β€” autonomously.

03

Clinical Output

Receive a precision heatmap and structured report. Normal slides are cleared. Suspicious ones are escalated with priority flags.

The Team

Built by Researchers Who Know the Lab.

We are bioinformaticians, ML engineers, and clinicians β€” not consultants. We have worked in pathology labs and understand the real workflow.

BP

Bibhu Prasad

Founder & ML Lead

Graduate bioinformatician with hands-on experience working alongside clinical pathologists. Specialises in computational pathology, deep learning pipelines, and WSI analysis.

Bioinformatics Computational Pathology Deep Learning WSI Analysis
M2

Member 2

Co-Founder & Genomics Lead

Specialist in next-generation sequencing and whole genome sequencing with extensive experience handling clinical genomic datasets and translating sequencing data into actionable clinical insights.

NGS WGS Clinical Data Genomics