Rig Comparisons: See How It Stacks Up

The standard framework for building LLM applications with comprehensive tool integration, memory management, and agent orchestration capabilities.

CrewAI is an open-source Python framework for orchestrating autonomous AI agents that collaborate as a team to accomplish complex tasks. You define agents with specific roles, goals, and tools, then organize them into crews with defined workflows. Agents can delegate work to each other, share context, and execute multi-step processes like market research, content creation, or data analysis. CrewAI supports sequential and parallel task execution, integrates with popular LLMs, and provides memory systems for agent learning. It's one of the most popular multi-agent frameworks with a large community and extensive documentation.

LlamaIndex: Data framework for RAG pipelines, indexing, and agent retrieval.

Production-grade Python agent framework that brings FastAPI-level developer experience to AI agent development. Built by the Pydantic team, it provides type-safe agent creation with automatic validation, structured outputs, and seamless integration with Python's ecosystem. Supports all major LLM providers through a unified interface while maintaining full type safety from development through deployment.

Lightweight Python framework for building AI agents with Pydantic schema validation, modular design, and provider-agnostic architecture. Build type-safe agent pipelines without framework overhead.

Revolutionary open-source AI framework enabling self-building autonomous agents that generate their own functions, track dependencies, and expand capabilities automatically. Perfect for AI research, educational projects, and experimental development.

Open-source Python framework for building reliable AI agents and stateful applications as visual state machines, featuring built-in telemetry UI, pluggable persistence, and Apache Software Foundation governance for production-ready development.