Raven integrates an AI engine into Grasshopper, enabling users to create or modify parametric node graphs through natural‑language or image prompts. The system automatically generates compatible definitions across 900+ plugins, supports team naming conventions, and offers an interactive chat for iterative refinement, with enterprise options for data isolation and one‑click deployment to ShapeDiver.
Funding
Funding not disclosed
Founders
Product
Problem
Parametric design in Grasshopper requires extensive scripting expertise and manual iteration, leading to long development cycles and limited scalability for design teams and educators.
Solution
Raven embeds an AI engine directly into the Grasshopper environment, allowing users to describe geometry or workflow intent via natural‑language text or images. The system translates these prompts into functional Grasshopper definitions, automatically wiring nodes and configuring component parameters. It maintains full compatibility with the existing plugin ecosystem—supporting over 900 third‑party components—and respects project‑specific scripting conventions. A built‑in chat interface enables iterative refinement and collaborative discussion, while enterprise‑grade options provide data isolation, single sign‑on, and custom licensing. The platform also integrates with ShapeDiver to generate deployable web applications from the generated scripts.
Target Audience
Primary users are architects, engineers, and industrial designers who develop parametric models in Rhino/Grasshopper, as well as design firms and academic programs seeking to accelerate CAD workflows and upskill teams.
Features
- AI‑driven code generation that creates or edits Grasshopper node graphs from plain‑text or image prompts.
- Seamless interoperability with 928+ Grasshopper plugins and user‑defined components, without requiring additional configuration.
- Interactive chat window for real‑time prompt refinement, script explanation, and collaborative troubleshooting.
- Context‑aware scripting that adheres to team‑defined naming conventions, documentation standards, and version‑control workflows.
- Secure, HIPAA‑level data handling with optional on‑premise data silos, SSO integration, and Azure/OpenAI enterprise APIs for confidential projects.
- One‑click deployment to ShapeDiver, enabling instant generation of parametric web apps from the AI‑produced definitions.
- Usage metering based on inference compute (prompt tokens, conversation turns, canvas context) with configurable limits for hobby, professional, and enterprise plans.