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Raven

AI-powered Grasshopper script generation from text and images

Native AI assistant for Grasshopper that generates, edits, and iterates parametric scripts from natural language prompts and reference images. Born from UC Berkeley research, deployed as a Rhino plugin with deep Grasshopper API integration.

Not publicly specified raisedGrowth Stage
Founded 2023 · 3,600+ active users, 6,623 downloads on Rhino Package Manager
Website →← All Tools
WHY IT EXISTS

Why This Tool Exists

The Problem

Architects and parametric designers spend hours writing Grasshopper scripts to explore design variations. Each iteration requires manual coding, debugging, and component assembly. Designers without strong programming skills struggle with script logic, limiting design exploration and increasing delivery time.

The Solution

Raven interprets natural language prompts and reference images to generate complete Grasshopper definitions. Users iterate by asking Raven to modify parameters, replace components, or reorganize logic. The AI understands both the canvas state and user intent, enabling rapid design exploration without manual coding.

USAGE

How You Use It

Delivery Method
Plugin
Integrations
Rhino 8GrasshopperShapeDiver928+ Grasshopper plugins
Disciplines
Architecture, Civil Engineering
Workflows
Data & Automation
Project Phases
Pre-Design, Schematic Design, Design Development
Project Types
Commercial, Residential, Infrastructure, Mixed-Use
TRANSPARENCY

Data Transparency

Exactly what this tool uses and how

Input
What it needs
Required:Natural language prompt or reference image
Optional:Existing Grasshopper definition for iteration, Design constraints or parameters, Custom coding conventions
Formats:Text descriptions, PNG/JPG images, .gh Grasshopper files
Output
What you get
Format:Grasshopper definition file with components and connections
Fields:Parametric script, Component assembly, Logic flow, User-owned IP in generated scripts
Algorithm
How it works
Model:Proprietary generative model (research-backed; specific LLM not disclosed)
Accuracy:Not publicly specified (claims rapid convergence to user intent through conversation)
Privacy
How your data is protected
Retention:Data retained only as long as necessary for service delivery
Training:On Free and Personal plans, user prompts and context data are used to deliver and improve services. To opt out of training and service-improvement use entirely, a Professional or Enterprise subscription is required. Generated scripts are owned by users with no attribution required.
Compliance:GDPR compliant, Swiss nFADP compliant, Does not knowingly process special-category data, Children under 16 not permitted
API
Integration
Endpoint:Contact vendor for API access
Method:Not publicly documented
USE CASES

Use Cases

  • ·Early-stage massing studies with rapid iteration (80% time savings reported)
  • ·Facade and parametric curtainwall system design
  • ·Site planning and generative landscape layouts
  • ·Structural optimization of geometric patterns
  • ·Real estate feasibility studies with automated design variations
PRICING

Pricing

Free
Free — $0, 300 monthly tokens, all core Raven features, community support
Personal
Personal (recommended) — $49/mo, 7K daily tokens, private context profiles, Python & C# components, Discord/DM support
Professional
Professional — $99/seat/mo, 200,000 monthly tokens/seat, data-training opt-out, shared team context, up to 5 team members, email support
Student
Student — 3,500 tokens with proof of active enrollment, public context profiles
Enterprise
Enterprise — custom pricing; pooled usage, centralized user management, invoice/PO billing, dedicated account management
Sources & Research NotesResearch date: 2026-02-01
Data Sources (8)
Fields Checked (16)
problem, solution, deliveryMethod, integrations, disciplines, projectPhases, projectTypes, maturityStage, input-output-specs, algorithm-approach, privacy-policy, compliance-gdpr-swiss, pricing-hobby-pro-enterprise, useCases, customerBase, control-features
Not Found (10)
funding-amount, specific-yearFounded, detailed-llm-model-name, api-rate-limits, data-retention-days, soc2-certification, iso27001-certification, detailed-accuracy-metrics, webhook-support, detailed-custom-integrations-beyond-shapediver
About this research: This record summarizes the cited sources and fields checked. A research date does not establish hands-on testing. Consult the original sources for current details and limitations.
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