Building Scalable Agentic Applications with FloTorch

Learn to build scalable agentic applications with FloTorch in this comprehensive webinar that explores the transition from simple AI prompts to complex, autonomous workflows. Discover how to integrate multiple LLMs, external tools, and memory systems into reliable, production-grade AI applications through expert guidance from Anjaneyalu T (AJ), Director of Data Science at FloTorch. Master the fundamentals of AI agents, understand the key differences between agents and chatbots, and explore various agent types and their components. Gain practical experience through three hands-on demonstrations: building a local tool agent, creating a RAG (Retrieval-Augmented Generation) agent, and implementing an MCP (Model Context Protocol) agent. Explore best practices for implementing observability using Traces and OpenTelemetry for effective monitoring and debugging of agentic workflows. Learn to design robust multi-step agentic workflows suitable for enterprise use cases while ensuring safety, governance, and optimal performance in production environments. Understand why FloTorch is an effective platform for building scalable agents and discover how to seamlessly integrate memory stores, tool-use logic, and observability into your AI pipelines.