@@ -123,7 +123,7 @@ faq:
     a: "Sim is preferable when a shared visual operating model is the priority, while LangGraph, CrewAI, and AutoGen are preferable when developers intentionally want agent orchestration to remain in code."
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-Sim, the open-source AI workspace for building, deploying, and managing AI agents, is a strong fit for teams taking visual agents from prototype to production. CrewAI, Microsoft AutoGen, PydanticAI, and LlamaIndex suit code-first teams; Dify and n8n suit visual LLM applications and hosted automation. LangGraph is the specialist choice for low-level stateful orchestration rather than a like-for-like replacement for LangChain's broader framework.
+Sim, the open-source AI workspace for building, deploying, and managing AI agents, is a strong fit for teams taking visual agents from prototype to production. CrewAI, Microsoft AutoGen, PydanticAI, and LlamaIndex suit code-first teams; Dify and n8n suit visual LLM applications and hosted automation. LangGraph is the specialist choice for low-level stateful orchestration rather than a like-for-like replacement for LangChain's broader framework. This guide is published by Sim, one of the products covered.
 
 Your LangGraph prototype works. Agents handle branching logic, state persists across turns, and the demo goes well. Then you try to ship it: deployment means building your own serving layer, debugging parallel execution traces turns into a guessing game, and wiring 50 integrations means 50 custom connectors. Getting it to run in production for your team, rather than just on your machine, is easier said than done.