Exploring AI's Role in Streamlining Rhino/Grasshopper Workflows

Rhino AI
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Hi everyone,

I’ve been loving Rhino for its versatility in surface modeling, SubD, and parametric design with Grasshopper. However, like many users, I occasionally run into small UI idiosyncrasies that disrupt my workflow. For example, today I spent 10 minutes patching a tiny gap created by the Shell command—a task that feels like it should be automated. This got me thinking: How might AI reshape the future of CAD interfaces to address these pain points?

Recently, I’ve noticed AI tools gaining traction in rendering, topology optimization, and concept visualization, but I’ve yet to see meaningful integration into core CAD workflows. Rhino’s command-line interface seems uniquely positioned to leverage AI, given its conversational nature. Imagine an AI assistant that lets you:

  • Point to a problem area (e.g., a gap) and say, “Patch this with a 2mm tolerance.”
  • Convert vague design intent (“Make this smoother”) into SubD tweaks or Grasshopper logic.
  • Automatically resolve errors like naked edges or non-manifold geometry.

Questions for the Community:

  1. Are there existing AI experiments or plugins (for Rhino/Grasshopper) that actively assist with modeling tasks like surface repair, parametric scripting, or error correction?
  2. How do you envision AI changing your workflow? Could it democratize advanced tools for non-experts, or simply accelerate existing processes?
  3. What strategies should McNeel prioritize to integrate AI? For example:
  • NLP-enhanced command line (e.g., conversational prompts).
  • AI-driven troubleshooting (auto-diagnose/fix modeling errors).
  • Generative design plugins for Grasshopper.

As someone who values Rhino’s expressiveness but craves smarter automation, I’d love to hear your thoughts!

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You might want to check this thread: Training AI on Rhinocommon using RAG

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Hey Aras,

I’m currently trying to shape an LLM that will generate, fix and streamline code for Grasshopper components. I’ve had various levels of success, but nothing that’s mature enough to share. It’s probably a way off from what you are looking for, because, for what I do, building the tools rather than the final data is the target.

I’ll hopefully be able to share my RAG set-up on the thread that @nathanletwory shared. But creating datasets for LoRA is taking longer to figure out than I had hoped. So the super AI solution that will replace the designer still remains in the distant future. :sweat_smile:

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