CrewAI

CrewAI is a standalone, lightweight Python framework purpose-built for orchestrating multiple AI agents that work together like a team. Rather than treating an LLM as a single conversational endpoint, CrewAI lets you assemble a 'crew' of specialized agents — each with a defined role, goal, and backstory — that hand tasks to one another and collaborate to solve problems a single agent would struggle with. The framework is organized around three core primitives: Agents, Tasks, and Crews. You define agents (who they are and what they can do), assign them tasks (the concrete work to complete), then orchestrate them inside a crew (the process and order of collaboration). On top of this, CrewAI Flows let you chain crews and add conditional logic for more sophisticated, event-driven workflows. Because it is a pure orchestration layer, CrewAI is model-agnostic: you point each agent at any LLM provider (OpenAI, Anthropic, local models via Ollama, and more) and equip them with arbitrary tools — web search, code execution, custom APIs. Developers choose CrewAI for its simplicity and focus. Unlike heavier frameworks that try to do everything, it stays lean and fast, making multi-agent systems approachable: a working crew can be defined in a few dozen lines of Python. The project has grown one of the largest communities in the agentic-AI space (tens of thousands of GitHub stars), with an active ecosystem of examples, integrations, and a hosted CrewAI Enterprise platform for teams that want managed deployment, tracing, and observability without running the framework themselves. CrewAI is a strong fit for research, content production, data enrichment, and any workflow that benefits from decomposing a job across specialized collaborating agents.