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Pricing sourced from Rig · Last verified March 2026
Detailed feature comparison coming soon. Visit Rig's website for complete plan details.
View Full Features →Choose Rig when you need performance, type safety, and low memory footprint — API servers handling thousands of concurrent requests, embedded systems, or when reliability is paramount. Choose LangChain for rapid prototyping and ecosystem breadth.
Yes, through the OpenAI-compatible API. Point Rig's OpenAI provider at Ollama's endpoint for local model development.
Rig is used in production by several companies. The API is stabilizing but still evolving. Check the latest version for breaking changes.
Rig focuses on single-agent pipelines with tool use. Multi-agent orchestration can be built on top using Rig's composable pipeline system and Tokio's async primitives.
The standard framework for building LLM applications with comprehensive tool integration, memory management, and agent orchestration capabilities.
Compare Pricing →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.
Compare Pricing →LlamaIndex: Data framework for RAG pipelines, indexing, and agent retrieval.
Compare Pricing →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.
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