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BrightInsight Regulated Digital Health Platform

Problem Space

Build and maintain a global regulated SaaS platform for digital health products with multi-cloud deployment (AWS, Azure, GCP) and regulatory compliance. Enable secure-by-default data handling across biopharma and medtech partners. Integrate early-stage ML/LLM capabilities for predictive clinical models while maintaining composability across 8 global engineering teams.

Architecture & Patterns

  • Modular microservice architecture spanning AWS, Azure, and GCP — secure-by-default
  • Self-describing APIs and composable platform modules
  • Integrated early-stage LLMs for predictive models for patient deterioration
  • Embedded contract testing (Pact) across 8 global teams — composable contracts let specialist teams move independently without a coordination tax
  • CI/CD pipelines with DevSecOps gates via GitHub Actions, Terraform, and Ansible
  • ML model training and tracking with PyTorch, TensorFlow, MLflow, and Delta Lake

Tools & Stack

Go, Node.js, TypeScript, C#, Pact, Terraform, Ansible, GitHub Actions, AWS, Azure, GCP, PyTorch, TensorFlow, MLflow, Delta Lake

Business Outcomes

  • 25% improved detection of patient deterioration via early-stage LLM predictive models
  • Over 20 million API calls per day across the platform
  • Embedded contract testing across 8 global teams reduced integration failures
  • Strengthened audit readiness via ISO 13485 and IEC 62304 mapping

Regulated / Domain Context

ISO 13485, IEC 62304 — medical device software lifecycle and quality management

Reusable Narrative Snippets

Built a global health data platform spanning AWS, Azure, and GCP with modular microservice architecture and secure-by-default design, serving over 20 million API calls per day.

Integrated early-stage LLMs for predictive models that improved patient deterioration detection by 25%.

Embedded contract testing with Pact across 8 global teams and introduced self-describing APIs and composable platform modules.

Source Notes

  • Derived from role responsibilities and achievements in config/madu_profile.json; reconciled with JobVia export (madu_alikor_export.json).
  • Confidence: high