Llama Deploy enables you to transform your LlamaIndex data indexes into production-ready AI agents. By configuring deployment targets such as AWS Lambda, Vercel Functions, or Docker containers, you get secure, auto-scaled chat APIs that serve responses from your custom index. It handles endpoint creation, request routing, token-based authentication, and performance monitoring out of the box. Llama Deploy streamlines the end-to-end process of deploying conversational AI, from local testing to production, ensuring low-latency and high availability.

BeeAI Framework provides a fully modular architecture for building intelligent agents that can perform tasks, manage state, and interact with external tools. It includes a memory manager for long-term context retention, a plugin system for custom skill integration, and built-in support for API chaining and multi-agent coordination. The framework offers Python and JavaScript SDKs, a command-line interface for scaffolding projects, and deployment scripts for cloud, Docker, or edge devices. Monitoring dashboards and logging utilities help track agent performance and troubleshoot issues in real time.