In response to increasing demand for highly detailed and fast medical imaging, HV initiated a modernization initiative to automate and scale their 3D modeling lab. The objective was to eliminate time-consuming manual operations and meet the growing needs of hospitals and medical researchers for rapid and compliant visual outputs. Our role was to help HV build a fully automated, compliant, and resilient cloud-based infrastructure capable of handling compute-intensive simulation workloads while adhering to healthcare data regulations.
Analyzed manual touchpoints across the 3D modeling lifecycle and automated each stage—from medical image ingestion to rendering output—using a combination of AWS Step Functions, S3, and containerized workloads. This led to faster processing and reduced dependency on human input.
Built a cloud infrastructure conforming to HIPAA standards using encrypted storage, fine-grained IAM policies, VPC isolation, and centralized audit logging. This ensured secure handling of sensitive health data and prepared the platform for regulatory reviews.
Provisioned dynamic compute clusters using AWS Fargate and EC2 Auto Scaling to handle rendering and simulation workloads in parallel. This enabled the platform to efficiently support increasing demand without over-provisioning.
Implemented continuous monitoring of system health, model accuracy, and processing throughput using AWS CloudWatch and custom dashboards. Alerting was configured to notify the team of anomalies in real-time, helping to maintain consistent output quality.
The engagement began with mapping out the existing manual 3D modeling workflows, identifying friction points that affected production speed and scalability. We then designed a fully automated cloud-native pipeline, orchestrating tasks such as image ingestion, model generation, and post-processing using containerized workloads and serverless triggers. To meet strict healthcare compliance standards, we implemented an architecture aligned with HIPAA requirements, ensuring full encryption, audit logging, and controlled access. Additionally, high-performance computing environments were provisioned to run simulations in parallel, significantly reducing total processing time. A dedicated monitoring layer was set up to maintain quality control across model accuracy, system availability, and performance over time.
Manual Workload Reduction
Processing Speed Increase
Compliance Readiness
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