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Text-to-CAD

Introduction: Zoo's Text-to-CAD transforms natural language into editable CAD models using machine learning, featuring B-Rep outputs compatible with SolidWorks, Fusion 360, and Blender. Explore its freemium model and API integration for accelerated design workflows.

Pricing Model: Freemium (40 free minutes/month + $0.50 per minute thereafter) (Please note that the pricing model may be outdated.)

Generative AICAD Modeling3D DesignParametric DesignManufacturing Tech
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In-Depth Analysis

Overview

  • AI-Powered CAD Generation: Text-to-CAD by Zoo.dev transforms natural language prompts into editable B-Rep CAD models using machine learning algorithms trained on parametric design principles.
  • Cross-Platform Compatibility: Generates industry-standard STEP and GLB files compatible with major CAD software (SolidWorks, Fusion 360) and 3D modeling tools (Blender), maintaining full editability in target applications.
  • Parametric Design Foundation: Produces boundary representation (B-Rep) models rather than mesh-based geometries, preserving precise dimensional control critical for manufacturing workflows.

Use Cases

  • Mechanical Component Drafting: Rapid generation of standardized parts like helical gears (36+ teeth configurations) and impeller blades (8-12 vane variations) from technical descriptions.
  • Educational Prototyping: Engineering students create functional mechanisms (linkages, bearing housings) without advanced CAD modeling expertise.
  • Design Iteration Acceleration: Product teams generate multiple concept variations (corner radii iterations, hole pattern alternatives) through prompt modifications.
  • Localization Support: Processes non-English prompts (French/Spanish technical terms) for international engineering teams.

Key Features

  • Multi-Format Export: Automatically outputs both STEP files for CAD editing and GLTF files for 3D visualization in a single generation process.
  • API-Driven Customization: Provides Python SDK for programmatic integration with custom design workflows through KittyCAD's machine learning endpoints.
  • Prompt Optimization Engine: Supports technical specifications including tooth counts (e.g., 36-tooth gears), angular relationships (helical forms), and geometric constraints (hole patterns with positional tolerances).
  • Asynchronous Processing: Implements polling system with status checks to handle complex model generation requiring up to 5-minute compute times.

Final Recommendation

  • Essential for Hardware Startups: Particularly valuable for teams needing rapid concept iteration while maintaining DFM-ready file formats throughout development cycles.
  • Recommended for Engineering Education: Integrates with existing CAD curricula to teach design intent specification through structured prompt engineering techniques.
  • Optimal for API-First Organizations: Developers building custom CAE tools benefit from webhooks and Python integration for automated design pipelines.
  • Ideal for Cross-Disciplinary Teams: Facilitates collaboration between technical and non-technical stakeholders through visualizable CAD outputs from textual requirements.

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