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Trusted Medical Answers in Seconds with Context-Aware AI

Case Studies, AI & GenAI: Albert Hupa

Healthcare professionals need fast access to accurate medical information. But when knowledge is spread across multiple systems, databases, and medical resources, finding reliable answers can be time-consuming.

 

A leading pharmaceutical company set out to change that by creating a trusted AI experience built on connected medical knowledge. 

 

Client Profile:

The organization wanted to improve access to medical information for healthcare professionals, including product information, contraindications, adverse effects, drug interactions, and reimbursement status.

 

Challenge:

Medical information was distributed across disconnected sources, making it difficult to provide fast, reliable, and source-grounded answers. The company needed a solution that could connect fragmented knowledge, support regulatory requirements, and reduce the risk of unsupported AI responses. 

 

Three pharma employees in lab coats looking at a tablet.

 

Solution:

We implemented an Enterprise Context Layer on Microsoft Azure through our Contextual AI Factory, connecting trusted medical sources, business rules, and pharmaceutical relationships into a unified AI-ready foundation. The solution powers an AI Medical Assistant that delivers source-grounded answers with citations, a complete audit trail, and built-in governance controls. It can also surface relevant, compliant product education and promotional content based on the healthcare professional’s query. 

 

Impact:

By transforming fragmented medical knowledge into a connected context layer, the company gave healthcare professionals faster access to trusted information, created new opportunities for compliant, context-aware engagement, and established a scalable foundation for future AI innovation. 

 

Key results:

  • 90%+ benchmark accuracy rate across 300+ representative medical questions, with answers matching expected, source-verified content and containing no unsupported statements

  • Answers delivered in approximately 25 seconds

  • 24/7 access to trusted medical information

  • Source-grounded, auditable responses with citations and a complete audit trail

  • Designed to cost approximately $0.10 per query, supporting cost-efficient scalability  

  • Production-ready AI foundation for future healthcare AI use cases 

     

     
Albert Hupa
Albert Hupa DS&AI Consultant

Albert is a Data Science and AI leader with 14 years of experience helping organizations turn emerging technologies into business value. After earning a PhD focused on text mining, NLP, and social network analysis, he built deep expertise in knowledge graph reconstruction and advanced analytics. Today, he specializes in multimodal LLMs and enterprise AI adoption, championing an iterative, proof-of-concept-driven approach that enables organizations to learn quickly, validate opportunities, and scale successful solutions. With a strong background in e-commerce and retail, Albert has led complex data architecture and integration programs connecting digital commerce platforms, ERP systems, and enterprise data ecosystems.

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