Accelerated multi-modal medical research with an intelligent imaging platform

The Challenges
Fragmented workflows slowing down scientific breakthroughs

• Researchers, data scientists, and engineers faced siloed processes that hindered collaboration and slowed research cycles.
  
  
• There was an urgent need to automate image curation, annotations, and pipeline management to reduce manual overhead and increase reproducibility.
  
  
• The client required a robust platform capable of supporting diverse, multi-modal datasets, including imaging, omics, and EHR, while meeting GxP compliance.

The Solution
Experience-driven imaging platform built for scale and flexibility

Designed and engineered the experience layer of a powerful imaging research platform, featuring:

1. A common framework for packaging algorithms into deployable applications (for both internal and external use).
   
   
2. ML Ops workbench for training, deploying, and monitoring AI/ML models.
   
   
3. Gen AI-powered search tools and NLP-based pipelines for smarter data discovery.
   
   
4. Tools to search, access, and prepare multi-modal data from RAPYD systems.
   
   
5. Extended Open Health Imaging Foundation (OHIF) viewers to support specialized image formats and interaction needs.
   
   
6. Containerization of existing ophthalmology algorithms for deployment across varied environments.
   
   
7. FAIRified repository with anonymized, standardized, and annotated imaging studies to support cohort-based clinical research.

Cloud-native innovation powered by AWS

• Core AWS Services: S3, EC2, EKS, Redshift, SageMaker, Bedrock, CloudTrail, Lambda, and Step Functions.
  
  
• Custom DevOps Enablement: CI/CD pipelines, security audits, and infrastructure automation for scalable deployment.

The Value Delivered
Unified insights, accelerated research, better decisions