AI-Powered HealthTech: Developing a Cardiovascular Risk Assessment Platform
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The Challenge
The client needed to create a reliable, secure, and user-friendly web platform to enable public cardiovascular risk assessment. This required seamlessly integrating a complex machine learning model (TensorFlow) into a secure cloud environment (Azure), building API integrations, and delivering a dual front-end system: a marketing website with CMS flexibility and a separate, fast-updating web application. Key challenges included securely deploying and integrating a complex TensorFlow machine learning model onto a compliant cloud infrastructure, and coordinating infrastructure engineering, AI model integration, external API integrations, and professional UI/UX design into one cohesive product.
Our Approach
COCO Software provided comprehensive support, starting with founder strategy and culminating in a robust, multi-layered technical deployment:
- •Strategic Support & Infrastructure: Supported the founder to success on the Microsoft for Startups programme and built a secure, scalable infrastructure entirely on Azure.
- •AI & API Integration: Integrated the core TensorFlow model and built necessary integrations with various third-party APIs and services to ensure comprehensive functionality.
- •Design & Dual Front-end Development: Collaborated with a professional UI/UX designer on the user experience. The solution separated the front-end requirements: the marketing website was built on WordPress for easy CMS updates by the marketing team, and the complex web app was built using Lovable for fast future design updates and iteration.
The Outcome
The partnership resulted in the successful launch of a secure, AI-powered HealthTech platform with a flexible architecture designed for both performance and easy content management.
- •Successful support and completion of the Microsoft for Startups programme, validating the technical and business approach.
- •Launch of a secure and scalable platform built on Azure, capable of reliably running the integrated TensorFlow model.
- •Achieved architectural flexibility by using a dual-front-end solution (WordPress/Lovable) to separate marketing content from the core application logic.