Agentic AI for Scalable Healthcare Intelligence with SambaNova
This workshop demonstrates how agent-based AI systems can be used to unlock secure, real-time insights from complex healthcare data. Participants will explore a live architecture that combines LangGraph agents, multiple LLMs, and Neo4j graph databases to support advanced clinical reasoning and patient similarity search. It also highlights how SambaNova’s SambaStack enables efficient multi-model deployment on a single node, reducing infrastructure costs while supporting high-performance, production-ready healthcare applications.
Key insights you'll gain
How to design and orchestrate agentic AI workflows using LangGraph to handle complex, multi-step healthcare reasoning tasks.
How to integrate multiple LLMs with specialized tools for querying and analyzing real EHR data stored in Neo4j graph databases.
How to use embeddings and graph-based search to identify clinically similar patient profiles and support decision-making.
How SambaNova’s SambaStack enables efficient multi-model deployment on a single node for scalable, low-latency, cost-effective AI systems.
Instructor
Varun Krishna
Senior Principal Solutions Engineer | SambaNova Systems
Varun Krishna works on agentic AI systems and scalable LLM-based applications for healthcare, with experience in LangGraph, Neo4j, and SambaNova’s infrastructure.
What’s included
• Live q&a get your questions answered with Varun Krishna • Access to session recordings and the full slide deck • Discount on future workshops and advanced AI courses • Personalized feedback and practical tips from the instructor • Exclusive resources from SambaNova for deeper learning • Hands-on experience with building agentic AI systems