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Agentic AI Patient Analytics Platform for Healthcare Technology Provider Company

TuTeck Technologies built an AI-agentic self-service platform for a US-based AI research company, enabling doctors and healthcare assistants to interact with patient data through intelligent chat, predictive insights, and real-time analytics dashboards.

The Challenge

Rare disease research and clinical trials rely on complex and fragmented Electronic Health Record (EHR) data, making patient health analysis time-consuming and dependent on technical teams. Healthcare providers lacked self-service tools to explore patient data, generate insights, and receive predictive or prescriptive guidance in real time. The need was for an intelligent, secure, and scalable platform that could combine conversational AI with analytics while supporting clinical decision-making.

The Solution

TuTeck designed and implemented an AI-agentic platform that integrates conversational intelligence with self-service analytics. EHR data was ingested and processed using AWS data services and exposed through a robust analytical layer powered by Apache Superset. Generative AI models were integrated with Retrieval-Augmented Generation (RAG) to enable predictive and prescriptive chat interactions, allowing healthcare providers to query patient data, monitor health KPIs, and gain real-time insights without technical dependency.

Key Results

  • 30% faster reporting through self-service analytics and AI-driven insights
  • AI-agentic chat interface enabling real-time interaction with patient health data
  • Reduced dependency on technical teams for analytics and reporting
  • Flexible, self-service dashboards for customized patient data visualization
  • Seamless dashboard sharing across healthcare providers and research teams

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