> For the complete documentation index, see [llms.txt](https://alphaswarm-ai.gitbook.io/evonode.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://alphaswarm-ai.gitbook.io/evonode.ai/architecture.md).

# Architecture

## System Overview

EvoNode.ai's architecture is designed to provide a seamless, scalable, and efficient platform for deploying and orchestrating serverless AI agents.

**Core Components :**

* **AI Agent Orchestrator** : The orchestrator is the central hub that manages the lifecycle of all AI agents, from deployment to scaling and execution.
* S**erverless Execution Layer** : This layer is responsible for running AI agents in a serverless environment.
* **AI Agent Repository :** The repository holds pre-trained AI models, algorithms, and configurations.
* **Data Ingestion :** The data ingestion layer collects and processes incoming data from multiple sources (e.g., databases, APIs, real-time streams).
* **Real-time Data Processing :** Real-time data processing allows AI agents to receive, process, and act on data instantly.