AI-Ready Data Platform Accelerating Surgical Innovation

Overview

A newly public health tech company needed a unified, AI-ready data platform to strengthen surgical planning and clinical decision support. They sought help integrating diverse data sources, implementing secure de-identification, and enabling scalable ML workflows. ImagineX designed a modern Medallion Architecture on AWS, pairing automated pipelines with a custom UI to streamline labeling, enrichment, and analytics.

Problem

• Disconnected data sources limited AI model development and clinical insights.

• Lacked secure, compliant de-identification and PHI removal workflows.

• Manual labeling slowed dataset readiness for ML and LLM use cases.

• No platform for centralized enrichment, analytics, or clinical review.

• Needed a fast path to MVP to support executive timelines.

Solution

ImagineX built a secure AWS-based Medallion Architecture with automated ingestion from databases and image repositories. ETL pipelines cleaned, deduped, and de-identified data while a custom Next.js UI enabled human-in-the-loop labeling for pathology classification. The platform published refined Gold-layer datasets for analytics and AI use cases, including MS Teams chat ingestion for case summarization. Full Terraform IaC, clear documentation, and Agile delivery ensured rapid, scalable deployment aligned with clinical workflows.

Outcome

• Delivered an MVP aligned with executive speed-to-market goals.

• Enabled scalable AI, ML, and LLM development with cleaned/consolidated datasets.

• Unified data foundation improves surgical planning and business insights.

• Custom clinical UI streamlined labeling, enrichment, and data exploration workflows.

Services

• Technology Delivery

• Technical Management

• Agile Delivery

• Data & Software Engineering

Technologies Used

• AWS Glue

• AWS S3 (Delta Lake)

• AWS Step Functions

• AWS Bedrock

• Terraform

• Next.js UI