GCPProductionEvidence: Medium65/100

NIRAMAI Health Analytix AI-Powered Breast Cancer Detection

Use case typeMedical imagingUpdated Jun 13, 2026

NIRAMAI Health Analytix, an India-based healthcare startup, uses AI and machine learning to provide affordable, non-invasive breast cancer detection through thermal image analysis. The system analyzes thermal images with AI models deployed on Google Kubernetes Engine, enhancing screening accuracy and scalability.

Industry
Healthcare
Location
India

Reported outcomes

+90%

accuracyQuality & accuracy

+27%accuracy

Strategic outcomes

New product / capabilityAI-powered non-invasive breast cancer screeningScale & capacityBuilt a scalable screening systemMarket & geographic expansionExpanded screening installations in IndiaCustomer experience & trustImproved accessibility and affordability of screening
Why do we believe this?Outcome claims, sources, and evidence checks

Normalized claim

Accuracy: 90% increase

Google Cloud Customer StoriesCustomer storyInferred claimMedium evidence strength

Achieved 90% accuracy in breast cancer detection, 27% higher than mammography.

Normalized claim

Accuracy: 27% increase

Google Cloud Customer StoriesCustomer storyInferred claimMedium evidence strength

Achieved 90% accuracy in breast cancer detection, 27% higher than mammography.

Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
Customer
NIRAMAI Health Analytix
Provider
GCP
Maturity
Production

The system analyzes thermal images with AI models deployed on Google Kubernetes Engine, enhancing screening accuracy and scalability

Customer identity supportedSource describes one deploymentMaturity supported

Primary read

Use case focus

Showing 2 of 2

  • 1AI for Medical Imaging
  • 2Healthcare Diagnostics
  • Breast cancer detection is challenging for women with dense breast tissue where mammography is less effective.
  • Traditional mammography is expensive and radiation-based, limiting accessibility and frequent screening.
  • There was a need for a scalable, affordable, and non-invasive early detection method suitable for all women ages.
  • Deployed a thermal image analysis system using TensorFlow machine learning models containerized and managed on Google Kubernetes Engine for scalability.
  • Uses AI models to extract features from thermal images and produce diagnostic reports for doctors.
  • Participated in Google's Launchpad accelerator program to enhance scalability, user interface, and business model.
  • Relies on continual model retraining to improve accuracy and reduce false positives/negatives.
  • Achieved 90% accuracy in breast cancer detection, 27% higher than mammography.
  • Supported over 25 installations in India with plans for international expansion.
  • Improved accessibility and affordability of breast cancer screening, including outreach in non-traditional locations like shopping malls.
  • Received clinical validations, regulatory preparation, and venture funding for scaling operations.
Sources & evidence1
Evidence: Medium65/100Evidence strength
  • Customer explicitly identified
  • Deployment status explicitly supported
  • Primary source available
  • Quantified outcome available
  • Technical implementation details available
Type: Customer StoryPublisher: Google Cloud Customer StoriesEvidence: PrimaryConfidence: High

AI-generated summary. Verify important details with the linked sources before relying on this case.

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