Mr. Hirenkumar Dholariya

AI Driven Data Modernization for Decision Support in Healthcare

Abstract:

 Healthcare and life sciences organizations manage large volumes of unstructured, multilingual, and mission critical data across clinical systems, laboratory environments, and service operations. This session describes an enterprise scale AI driven virtual assistant designed to address challenges such as fragmented historical data, slow decision cycles, incomplete recommendations, and operational constraints in regulated healthcare and life sciences environments.

The solution follows a three layer architecture consisting of a Data Foundation Layer, a Semantic Processing Layer, and a Retrieval and Response Layer. The Data Foundation Layer consolidates enterprise data sources including service histories, equipment metadata, manuals, and troubleshooting records into unified datasets suitable for analytics and retrieval. The Semantic Processing Layer applies large language model based techniques to translate, summarize, normalize terminology, and generate vector embeddings while preserving domain specific meaning. The Retrieval and Response Layer supports semantic search and retrieval augmented generation to provide context relevant responses for field engineers, laboratory technicians, and support teams.

The platform is used to support operational workflows by improving access to historical information and validated troubleshooting guidance. It is designed to reduce manual search effort and support decision making in service and laboratory environments.

A compliance focused approach incorporates audit trails, data lineage, access controls, and governed prompt usage to support responsible AI deployment in regulated settings. The system is evolving beyond information retrieval toward additional capabilities such as predictive maintenance and broader enterprise decision support use cases.

This session presents an implementation focused overview of how AI driven data modernization can support reliable decision making in healthcare and life sciences organizations.

Profile:

Hirenkumar Dholariya is a Senior Data Engineering Architect with 18+ years of experience supporting global Fortune 500 organizations, delivering up to 40% system performance improvement and 20–35% infrastructure cost reduction through AI-driven data engineering and cloud modernization. He specializes in AI-driven data engineering, automation, and cloud-based enterprise platforms, with a focus on scalable, governed, and real-time analytics.

He has led large-scale cloud modernization initiatives, architected AI-driven platforms such as Gene.AI, and designed intelligent data ecosystems integrating semantic intelligence and real-time decisioning. His leadership emphasizes innovation and collaboration, delivering scalable data solutions that enhance decision-making and operational excellence. He regularly shares practical insights on enterprise AI modernization, cloud architecture, and responsible AI adoption.