Speaker

Martina D'Antoni

Martina D'Antoni

KBMS - Software Engineer

Rome, Italy

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I hold a Bachelor’s degree in Clinical Engineering and a Master’s degree in Biomedical Engineering. Since 2021, I have been working as a Software Engineer in the healthcare sector, where I combine my clinical background with strong technical expertise.

Over the years, I have gained solid experience in designing and developing web applications using ASP.NET, performing advanced data analysis, and integrating Artificial Intelligence solutions into clinical workflows. My work focuses on building reliable, scalable, and impactful digital tools that enhance healthcare processes and support data-driven decision-making.

I am passionate about leveraging technology to improve patient care, optimize clinical operations, and bridge the gap between engineering and medicine.

Area of Expertise

  • Health & Medical
  • Information & Communications Technology

Topics

  • Software Deveopment
  • ASP.NET Core
  • Data Engineering
  • Biomedical Informatics
  • RabbitMQ
  • Web Apps
  • SemanticKernel
  • OpenAI
  • Azure OpenAi
  • SQL Sever
  • LangChain
  • GPT
  • RAG
  • .NET
  • FullStack Development

Building an Agentic RAG Pipeline

Traditional Retrieval-Augmented Generation (RAG) combines external data with generative models, but Agentic RAG takes this a step further by using intelligent agents to refine queries and enhance results. These agents independently manage the retrieval and generation process, improving accuracy and relevance through iterative querying and self-correction. In this talk, we’ll compare standard RAG with Agentic RAG, demonstrating how the agent-driven approach provides greater flexibility, scalability, and performance for complex, real-world tasks. Learn how to implement Agentic RAG to optimize AI-driven systems for more sophisticated and accurate results.

Martina D'Antoni

KBMS - Software Engineer

Rome, Italy

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