Summary

Abbott's Neuromodulation Division, a leader in advanced neurostimulation therapies for chronic pain and movement disorders such as Parkinson’s, partnered with HCLTech to transform its digital health infrastructure using comprehensive Microsoft Azure technologies.

The Challenge

Abbott's Neuromodulation Division faced critical challenges in a competitive medtech landscape dominated by major players like Medtronic and Boston Scientific. Key obstacles included navigating complex global healthcare regulations, ensuring product differentiation for innovative therapies like DRG stimulation, maintaining rigorous safety compliance for implantable devices, and driving physician adoption of newer neuromodulation modalities.

Critically, the division also needed to integrate secure digital care and remote monitoring capabilities while safeguarding patient data and ensuring seamless interoperability with diverse healthcare systems across multiple markets.

The Objective

Building on its commitment to improving patient quality of life through technology innovation, Abbott sought to modernize its digital health infrastructure to accelerate time-to-market, enhance global availability and strengthen security compliance. The goal was to create a scalable, secure platform that would support virtual clinic connectivity, streamline patient enrollment workflows and enable real-time communication between clinicians and patients while meeting stringent regulatory requirements for medical device data handling.

The Solution

HCLTech collaborated with Abbott NMD and delivered a comprehensive Microsoft Azure-based solution leveraging over 40 Azure resource types across Central US, East US, West US2, and Global regions, ensuring low-latency access and business continuity for clinicians and patients worldwide.

The solutions’ components include:

• Azure Key Vault, which safeguards sensitive credentials, while Network Security Groups, Private Endpoints, and Route Tables enforce strict access controls — critical for protecting patient data and meeting regulatory standards
• Azure App Services (with slots for zero-downtime deployments), Application Insights, and Log Analytics provide deep visibility into system health and user behavior, enabling proactive support and optimization
• Azure DevOps powers CI/CD pipelines with integrated unit and system testing (via PyTest), accelerating delivery cycles while maintaining quality
• Azure Functions and Event Grid support event-driven automation for backend workflows
• Azure Front Door and Traffic Manager intelligently route traffic based on health and geography — ensuring seamless user experiences across regions
• Apps are hosted in Azure WebApp Containers and distributed via App Center, while Azure Notification Hubs enable real-time communication with users

The Impact

The transformation delivered exceptional outcomes, reducing development cycles by 40% through Azure services integration and Azure DevOps automation. HCLTech’s solution for Abbott also enabled seamless virtual clinic connectivity with minimal latency, while operational efficiency improvements halved mean time to detect and resolve issues, helping clinicians enhance care for patients.

Other notable results include:

• Improved security: 100% data encryption with reduction in security incident risk achieved through Azure Key Vault and Network Security Groups
• Increased global performance by 30%: With 99.99% uptime, supporting round-the-clock clinical operations
• Reduced enrollment time: Modernizing patient enrollment workflows reduced enrollment time significantly and enhanced therapy program accessibility

The solutions’ scalable, repeatable architecture positions Abbott as a digital health leader while creating new pathways for patient-centered neuromodulation care delivery.

Summary

Kaiser Permanente, America's largest not-for-profit integrated healthcare provider serving millions of patients, partnered with HCLTech to transform clinical decision-making for 24,000 physicians. HCLTech developed the Clinical Advisor, an advanced agentic platform using Azure AI Foundry, that transforms complex medical searches from 5-minute manual processes into instant, evidence-linked answers — dramatically improving patient care quality and physician satisfaction.

The Challenge

Kaiser Permanente physicians faced a critical operational bottleneck: navigating over 20,000 internal guidelines during 20-minute patient consultations required them to step away from direct patient interaction to undertake time-consuming manual searches averaging 5 minutes per query. Half of these searches were abandoned due to time pressures, creating clinical inconsistency risks, heightened physician burnout and — critically — diminished patient care quality.

This systemic challenge extended well beyond workplace efficiency. With the dual stress of providing accurate care while maintaining timely appointments, physicians frequently took unfinished tasks home to complete, encroaching on personal and family time, and further contributing significantly to burnout and dissatisfaction.

The Objective

The goal was clear: Kaiser Permanente needed to eliminate clinical information retrieval friction while maintaining the highest security and compliance standards. This meant restoring clinician time for direct patient care, reducing search abandonment rates and creating a scalable solution that could enhance clinical workflow efficiency across its vast healthcare network.

The Solution

Kaiser Permanente partnered with HCLTech to develop HCLTech Clinical Advisor using Azure AI Foundry — creating a secure, agentic clinical decision-support platform within Kaiser's Azure environment. Clinicians can instantly ask natural-language questions directly within their workflow and receive precise, evidence-linked answers and recommendations in mere seconds — not minutes. The solution provides inline citations, automated contextual medical calculators integrated with FHIR-based EHRs, and proactive next-best-action prompts. Built with Trustworthy AI principles, it features end-to-end encryption, least-privilege access, groundedness and protected-material checks, and full traceability through Azure Monitor and Log Analytics, ensuring PHI remains secure while delivering transformational clinical support.

Other Azure services utilized in the solution:

Microsoft Entra ID, Azure Subscription, Azure Private DNS, Azure DNS, Application Gateway, Azure Speech, Azure AI Search, Azure Key Vault, Azure Document Intelligence, Azure OpenAI Service, App Subnets, Private-Link Subnet, Azure Database for PostgreSQL, Application Insights and Container Insights.

The Impact

The launch of the HCLTech Clinical Advisor delivered exceptional results:

• Clinician time restored: Search time reduced from 5 minutes to under 2 minutes
• Reduced search abandonment: 50% decrease in abandoned searches
• Significant productivity gains: $50 million annual productivity gain equivalent to 15% consultation capacity increase
• Enhanced clinical workflow: Processing 440,000 monthly queries (5.2 million annualized) significantly improved physician satisfaction and work-life balance

Delivered as the HCLTech Healthcare Copilot Accelerator, the same RAG-plus-FHIR blueprint can be deployed in weeks for other health systems without reengineering core logic. The accelerator ships with modular agents (guideline Q&A, calculator, procedural checklists) that plug directly into Azure AI Foundry. It demonstrates the scalability of HCLTech solutions and positions Microsoft as the trusted partner for responsible clinical AI innovation.

Demo Reference

To view the full demo video of GenAI-powered Clinical Advisor click here.

Summary

Novartis, a global pharmaceutical leader, partnered with HCLTech to transform its patient safety monitoring capabilities. Using Microsoft technologies, HCLTech developed an AI-powered Anomaly Detection Engine that analyzes diverse data sources — from adverse event forms to social media — and enables real-time identification of safety signals, compliance issues and data privacy concerns across Novartis's global operations.

The Challenge

Novartis experienced challenges in identifying anomalies across various unstructured data sources such as emails, phone conversations, social media, and clinical documents. The previous system was unable to configure new anomaly detection rules for early recognition of adverse events, technical issues, inappropriate conduct, or data privacy concerns, which impacted processes related to patient safety monitoring and regulatory compliance.

The Objective

Novartis sought to improve patient safety surveillance with intelligent automation, aiming for a real-time anomaly detection system that processes varied data formats, reduces manual oversight, and enhances compliance across its global operations.

The Solution

HCLTech implemented a comprehensive AI-driven platform leveraging Azure OpenAI Service (GPT-4o) and Azure AI Document Intelligence for sophisticated anomaly detection. The solution incorporated responsible AI principles through secure Azure Key Vault credential protection and Azure AD (Entra ID) authentication. Azure Functions (Durable) and Logic Apps orchestrated real-time data processing across multiple channels, while Power Platform enabled intuitive dashboards and low-code workflow configuration. The platform was built using Python (with PyPDF2, Pydantic, Pandas, OpenAI, semchunk) and .NET (with Aspose, Azure SDKs, SQLClient), with Azure Webapp for Front End React Deployment.

Other Microsoft technologies utilized included:

• Azure Service Bus to ensure reliable processing queues
• Azure Blob Storage for file archiving
• Azure SQL Database for structured ICSR Data
• Azure Code Repository for CI/CD

The Impact

Microsoft technologies played a critical role in enabling this transformation, and the results highlight the impact that decision had:

• Improved data quality: Promptly identifying and addressing anomalies improved data quality by 50%
• Enhanced productivity: 70% reduction in manual effort
• Improved security: 50% enhancement in security and reliability
• Reduced costs: Operational expenses decreased by 40% through automated processes

With its reusable ML models, governance and security and low-code/no-code enablement, this modular, cloud-native, data-agnostic engine demonstrates significant market potential, being repeatable across healthcare, finance and manufacturing sectors globally.

Summary

Syneos Health, a leading clinical research organization, partnered with HCLTech to revolutionize its adverse event case intake process. HCLTech developed a generative AI-assisted platform leveraging Azure OpenAI and Document Intelligence to transform manual, sheer volume of data in diverse formats , error-prone, pharmacovigilance workflows into an automated, intelligent system that processes Individual Case Safety Reports (ICSRs) from diverse sources with unprecedented speed and accuracy.

The Challenge

Syneos Health faced critical operational bottlenecks in their pharmacovigilance operations: manual ICSR intake from emails, portals and scanned PDFs averaged 1-2 hours per case — creating significant delays in regulatory reporting. The process was highly error-prone, volume intensive, repetitive task, lacked multilingual NLP capabilities and couldn't scale during peak volumes surges, which risked impacting patient safety monitoring and regulatory compliance in the pharmaceutical industry.

The Objective

Syneos Health needed to modernize its pharmacovigilance infrastructure to eliminate manual processing bottlenecks, improve case quality and compliance with regulations, and create a scalable solution that could handle fluctuating volumes while maintaining strict compliance standards for adverse event reporting.

The Solution

HCLTech implemented a comprehensive Gen AI platform using Azure OpenAI Service (GPT-4o) and Azure AI Document Intelligence for real-time adverse event extraction. The solution employed responsible AI principles through secure Azure Key Vault credential management and Azure AD (Entra ID) for secure authentication. Azure Functions (Durable), Logic Apps, and Service Bus orchestrated automated workflows, while Power BI provided analytics dashboards in a multi-tenant environment.

The platform was built using Python (with PyPDF2, Pydantic, pandas, OpenAI, semchunk) and .NET (with Aspose, Azure SDKs, SQLClient). Other Microsoft Azure technologies utilized included:

• Azure Blob Storage for file archiving
• Azure SQL Database for structured ICSR data
• Azure Webapp for Front End React Deployment
• Azure Code Repository deployed for CI/CD

The Impact

Key highlights for Syneos’ pharmacovigilance transformation include:

• Reduction in time and costs: 65% reduction in case processing time, with a 50% cost reduction per case
• Improved case quality: 40% improvement in case quality through auto-filled data
• Complete compliance: 100% compliance with data retention requirements while maintaining scalability
• Responsible AI principles: Emphasized through secure Azure Key Vault and Entra ID authentication

This modular framework demonstrates significant market potential, being repeatable across pharmaceutical sponsors, CROs and medical device manufacturers globally.

Demo Reference

To view the full demo video of GenAI assisted case intake platform click here.

Summary

UnitedHealth Group (UHG), a Fortune 3 healthcare enterprise, partnered with HCLTech to modernize its critical data infrastructure. HCLTech led a comprehensive migration from legacy Teradata systems to a cutting-edge Azure-based cloud platform, combining Azure, Databricks and Snowflake to create a scalable, cost-effective data ecosystem that enhances healthcare analytics and patient outcomes.

The Challenge

UHG faced significant resiliency and cost challenges with its aging Teradata on-premises platform. To deliver timely insights for patient care decisions and operational efficiency in an increasingly data-driven healthcare environment, UHG needed to a new solution. Careful analysis of the legacy infrastructure revealed the need to minimize business risks and disruptions, as well as the requirement to scale resources for migration from Teradata.

The Objective

UHG sought to future-proof its data infrastructure while maintaining operational continuity. This would require a smooth and successful transition. The project ultimately aimed to eliminate technical debt, reduce operational costs and democratize data access across the organization. It was designed to position UHG for enhanced healthcare analytics capabilities and improved patient outcomes through faster, more reliable data insights.

The Solution

HCLTech implemented a comprehensive framework-based migration approach, leveraging Microsoft Azure as the foundation with integrated Databricks and Snowflake capabilities. The solution emphasized responsible AI principles through secure data governance and ethical analytics practices. This cloud-first architecture enabled real-time healthcare analytics while maintaining HIPAA compliance and ensuring data security throughout the migration process.

The Impact

The transformation delivered exceptional results:

• Migration at scale, with 2.2 PB of data successfully migrated
• Data democratization increased by 30% through improved access, while eliminating technical debt from legacy systems
• 40% workload reduction in the Teradata workload 

This scalable framework approach demonstrates repeatability across the Health & Life Sciences sector, positioning both UHG and HCLTech for continued innovation in healthcare analytics and patient care optimization.