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Development of AI-Powered Big Data Analytics Platform for Sports & Wellness Biomarkers

acropolium

Health & Fitness

Medical

Sports

Challenges with Data Processing & Analysis

The client faced challenges with slow data processing speeds, inconsistent testing due to low stakeholder engagement in UAT, and limited communication with external developers, hindering timely solution delivery and impacting analysis accuracy.

About the Client

A targeted proteomics company providing research services and discovering novel biomarkers, specializing in sports and personal wellbeing using advanced proteomics methods.

Project Goals

Develop and deploy an AI & ML-integrated big data processing application.
Optimize the backend infrastructure for efficient data analysis.
Improve the accuracy of biomarker analysis.
Reduce the time required for data analysis processing.

System Functionality

Data ingestion and preprocessing from various sources.
AI/ML-powered biomarker identification and analysis.
Backend optimization for scalable data processing.
User-friendly graphical interface (Frontend).
Secure data storage and management.

Technology Stack

ReactJS

Python

NodeJS

AWS

External System Integrations

Potential integration with existing laboratory information management systems (LIMS).

Non-Functional Requirements

Scalability to handle large volumes of data.
High performance for rapid analysis.
Robust security measures to protect sensitive data.
Reliable and stable operation.

Expected Business Impact

This project is expected to reduce the time-to-market for new biomarker discoveries by 30%, increase analysis processing accuracy by 40%, and significantly reduce analysis processing time by approximately 38%. This will lead to faster research cycles, improved product development, and a competitive advantage in the sports and wellness market.