SwarmNode, founded by Bakar Tavadze, is a cloud-based platform that enables developers to run Python AI agents without managing servers, providing a serverless infrastructure for AI agent deployment and execution. ^{[2] [8]}

Overview

SwarmNode is designed to simplify the deployment and management of AI agents in the cloud. The platform eliminates the need for developers to handle server infrastructure, allowing them to focus solely on writing code for their AI agents. SwarmNode operates on a serverless model, similar to AWS Lambda but specifically optimized for AI-oriented applications. Developers can create, configure, and deploy AI agents that can be executed on demand or scheduled to run at specific times, with the platform handling all the underlying infrastructure requirements.

The project is built on the Solana blockchain, as indicated by its token (SNAI) being part of the Solana ecosystem. As of May 2025, SwarmNode has a market capitalization of approximately $18.3 million, with its SNAI token trading at around $0.02. ^{[1] [8]}

Key Features

Serverless Architecture

SwarmNode's core offering is its serverless infrastructure, which eliminates the need for developers to manage their own servers. This approach provides several advantages:

• No infrastructure management required
• Automatic scaling based on demand
• Pay-only-for-what-you-use pricing model
• Simplified deployment process
• Reduced operational overhead ^{[2] [1]}

Agent Chaining (Swarm)

One of the platform's distinctive features is the ability to chain multiple agents together to create a "swarm." This functionality allows:

• Agents to invoke other agents
• Creation of complex workflows through agent interaction
• Data passing between agents in a processing pipeline
• Building of sophisticated AI systems through component-based design

This chaining capability enables developers to build complex AI systems by connecting specialized agents, similar to an assembly line where each agent performs a specific task before passing results to the next agent. ^[2]

Persistent Data Storage

SwarmNode provides each agent with access to persistent and dedicated storage:

• Key-value datastore accessible to agents
• Data sharing capabilities between agents
• Persistence across agent executions
• No need to set up separate database infrastructure

This built-in storage solution eliminates the need for developers to configure and maintain separate database systems for their AI agents. ^[3]

Flexible Execution Options

The platform offers multiple ways to execute agents:

• Manual execution through the user interface
• Scheduled execution using cron expressions
• Programmatic execution via REST API
• Integration through Python SDK

This flexibility allows developers to trigger agent execution based on their specific requirements, whether that's on a regular schedule or in response to external events. ^[4]

Technical Implementation

Agent Structure

Each SwarmNode agent consists of three primary components:

1. Script: The Python code that defines the agent's functionality
2. Requirements: Any Python packages that the script depends on
3. Environment Variables: Configuration values accessible to the script during execution

The only mandatory component is the script, which must include a main function that serves as the entry point for execution. ^[5]

Development Process

The development workflow for creating and deploying agents on SwarmNode follows these steps:

1. Write a Python script with a main function
2. Specify any package dependencies in the requirements
3. Configure necessary environment variables
4. Deploy the agent to SwarmNode
5. Execute the agent manually or set up a schedule

The platform handles the building process, which includes setting up the environment with all specified dependencies. ^[5]

API and SDK Integration

SwarmNode provides both a REST API and a Python SDK for programmatic interaction with the platform:

import swarmnode
swarmnode.api_key = "YOUR_API_KEY"
agent = swarmnode.Agent.retrieve(id="AGENT_ID")
execution = agent.execute(payload={"foo": "bar"})

This allows developers to integrate SwarmNode capabilities into their existing applications and workflows. ^[6]

Use Cases

• Automated Data Processing: Scheduled agents that collect, process, and analyze data
• AI-Powered Automation: Agents that perform routine tasks with AI assistance
• Distributed AI Systems: Complex AI applications built from multiple specialized agents
• On-Demand AI Services: AI capabilities that can be invoked as needed without maintaining constant infrastructure
• Prototype Deployment: Quick deployment of AI prototypes without infrastructure setup ^[2]

Tokenomics

SwarmNode Token ($SNAI)

The SwarmNode ecosystem is powered by its native SNAI token, which operates on the Solana blockchain. Key metrics as of May 2025 include:

• Current Price: $0.02028
• Market Capitalization: $18.3 million
• 24-hour Trading Volume: $3.97 million
• Circulating Supply: 902.46 million SNAI
• Total Supply: 999.98 million SNAI ^{[1] [7]}