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Build and deploy LlamaAgents from scratch

LlamaIndex16 June 2026Watch on YouTube

Part of series

Ep. 8 · Agent Document Build

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Description

In this tutorial, you’ll learn how to go from idea to production using LlamaAgents, a powerful tool for deploying AI-driven workflows to the cloud. We’ll guide you step-by-step through creating and deploying an anomaly detection LlamaAgent, making it easy to bring intelligent automation into real-world applications. 🦙 Join the LlamaAgents waitlist: https://landing.llamaindex.ai/llamaagents?utm_source=youtube&utm_medium=li_channel 👩‍💻 View the Code on GitHub: https://github.com/AstraBert/anomaly-detection-workflow 📚 Learn More about LlamaAgents: https://developers.llamaindex.ai/python/cloud/llamaagents/getting-started/?utm_source=youtube&utm_medium=li_channel #LlamaAgents #AIworkflow #LlamaIndex

What you'll learn

  • You learn how to build an AI-workflow from idea to production using LlamaAgents
  • You discover the practical steps for deploying intelligent agents to the cloud
  • You see how anomaly detection is implemented in a working LlamaAgent project

Frequently asked questions

What is LlamaAgents and what can you do with it?
LlamaAgents is a tool that enables you to create and deploy AI-driven workflows to the cloud. It helps you implement intelligent automation in real-world applications, such as anomaly detection systems.
What practical example is used in the tutorial?
The tutorial demonstrates how to build and deploy an anomaly detection LlamaAgent. This working example illustrates how to put intelligent monitoring systems into production.
Where can you find the code and resources for this tutorial?
The code is available on GitHub via the AstraBert/anomaly-detection-workflow repository. You can also find more information in the LlamaIndex developers documentation and sign up for the LlamaAgents waitlist.

Topics

llama-indexagentsworkflow automationcloud deploymenttutorial