Building Agentic AI Workflows with FloTorch

Learn How to Build, Deploy, and Scale Agentic AI Workflows Using FloTorch

As organizations advance from building standalone AI agents to designing fully orchestrated, multi-step systems, the next frontier lies in creating Agentic AI Workflows – coordinated pipelines of intelligent agents working seamlessly together toward shared goals.

In this session, we’ll explore how FloTorch empowers developers and enterprises to design, execute, and monitor these agentic workflows – whether through code or via its intuitive no-code interface. FloTorch provides an integrated environment for connecting LLMs, tools, and APIs, making it easier to construct scalable, observable, and production-ready AI workflows.

We’ll begin by defining what an Agentic Workflow is and why it’s critical to the next wave of GenAI innovation. From there, we’ll demonstrate how FloTorch enables orchestration across multiple agents and models – both programmatically and visually – while maintaining visibility into runtime execution.

Participants will also discover multi-cloud patterns for deploying agentic workflows, ensuring interoperability and resilience across diverse environments. Through practical examples and demos, we’ll unpack how to move from conceptual agents to operational pipelines that deliver measurable outcomes.

What We Will Cover

• Understanding the fundamentals of Agentic AI Workflows and their role in scalable AI systems
• How to orchestrate agentic workflows in FloTorch using both code and no-code approaches
• Exploring multi-cloud and hybrid deployment patterns for AI workflows
• Managing runtime execution and observability for reliable performance
• Demonstrating real-world agentic workflow architectures in action

Hands-On Insights

Through live demonstrations and an interactive Q&A, attendees will gain practical knowledge of how to build and operationalize Agentic AI Workflows with FloTorch. You’ll learn how to design, orchestrate, and monitor intelligent agent pipelines – unlocking a deeper understanding of how agentic systems can be built, scaled, and governed efficiently.