Building Agentic AI with LangChain & LangGraph: From Single to Multi-Agent Systems

Agentic AI is revolutionizing AI systems by enabling autonomous reasoning, decision-making, and collaboration. In this webinar, we’ll explore how frameworks like LangChain and LangGraph empower developers to build dynamic AI agents. You'll learn to implement single-agent systems, such as AI assistants for CRM data management, and scale to multi-agent architectures for complex workflows, with insights from a Gartner case study. We’ll also cover integrating Retrieval Augmented Generation (RAG) to boost accuracy. Through hands-on demos, you’ll gain practical skills to design intelligent agents that enhance efficiency and transform business processes.

Key Takeaways:

• Introduction to Agentic AI – Understanding autonomous reasoning and decision-making.
• Building Single-Agent Systems – Developing an AI assistant for CRM data management.
• Multi-Agent Architectures – Exploring complex workflows with a real-world Gartner case study.
• Enhancing Contextual Understanding – Integrating Retrieval Augmented Generation (RAG) pipelines.
• Hands-on Demonstrations – Designing AI agents that retain context and collaborate efficiently.

A Data Scientist at Gartner, specializing in scaling Agentic AI for complex business challenges, with expertise in Machine Learning, NLP, and Gen AI. With 5+ years of experience, he designs intelligent agent systems using frameworks like LangChain and LangGraph to enhance enterprise decision-making. Currently pursuing a Master’s in AI at IIT Jodhpur, he holds a B.Tech in Computer Science from Manipal University. His expertise spans predictive modeling, AI agents, and cutting-edge AI applications. You can reach him on LinkedIn.