Agentic AI in Action: Deploying Secure, Task-Driven Agents in Rackspace Cloud
The concept of AI agents has emerged as a transformative tool, empowering organizations to create AI systems capable of secure, real-world interactions. By leveraging a language model’s natural language abilities alongside function-calling capabilities, an agentic AI system can interact with external systems, retrieve data, and perform complex tasks autonomously. Enterprises can harness the full potential of AI by designing agent workflows that interact securely with business data, ensuring control and privacy. In this post, we explore building an AI agentic workflow with Meta’s LLaMA 3.1, specifically crafted for interacting with private data from a database. We’ll dive into the technical foundation of agentic systems, examine how function calls operate, and show how to securely deploy all of this within a private cloud, keeping data secure.