AgentSmith is a modular agent orchestration framework built in Python that enables developers to define, configure, and run multiple AI agents collaboratively. Each agent can be assigned specialized roles—such as researcher, planner, coder, or reviewer—and communicate via an internal message bus. AgentSmith supports memory management through vector stores like FAISS or Pinecone, task decomposition into subtasks, and automated supervision to ensure goal completion. Agents and pipelines are configured via human-readable YAML files, and the framework integrates seamlessly with OpenAI APIs and custom LLMs. It includes built-in logging, monitoring, and error handling, making it ideal for automating software development workflows, data analysis, and decision support systems.

Swarms.ai is a collaborative AI agent orchestration platform designed to streamline complex workflows by allowing developers and business users to deploy multiple specialized agents that operate in parallel or sequentially. Each agent can be trained or configured for tasks like sentiment analysis, document summarization, market research, email outreach, and code generation. Users visually design workflows, connect agent outputs as inputs to the next step, and set conditional logic. Swarms provides real-time monitoring, logs, and performance metrics for each agent, enabling easy troubleshooting and optimization. With secure API integrations, multi-user collaboration, and role-based access, Swarms supports enterprise-scale deployments and can automate repetitive processes or generate insights at scale, reducing errors and manual overhead.