Locofy vs sizeless: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Locofy and sizeless — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
Locofy
Locofy.ai
AI design-to-code tool that converts Figma and Penpot designs into production-ready React, Vue, HTML-CSS, React Native, and Flutter code.
Key features
- Locofy Lightning: One-click AI conversion of Figma or Penpot designs into responsive, component-based frontend code using Large Design Models.
- Multi-Framework Export: Generates code for React, Vue, Angular, Next.js, Gatsby, HTML-CSS, React Native, and Flutter.
- Auto Components & Responsiveness: Automatically detects reusable components and makes layouts responsive across breakpoints.
- Design Tool Integration: Works as a plugin inside Figma and Penpot to convert designs without leaving the canvas.
- Agentic Dev Handoff: Acts as a frontend layer between design files and AI code editors like Cursor and Claude.
- Code Sync & Export: Pushes generated code to a repository or dev environment so design and code stay in sync.
Best for
- Rapid Prototyping: Convert a Figma mockup into a working frontend prototype in minutes instead of hand-coding it.
- Design-to-Dev Handoff: Hand developers clean, structured code generated directly from designer files.
- Frontend Acceleration: Cut UI coding time significantly when building React or React Native interfaces.
- Cross-Platform Builds: Generate both web and mobile UI code from a single design source.
- Legacy Workflow Modernization: Bridge existing Figma libraries into modern component-based codebases.
sizeless
sizeless
Turns a smartphone video of an open trench into a centimetre-accurate 3D point cloud, CAD as-built plan and GIS-ready digital twin of buried utilities.
Key features
- Smartphone capture: Field crews record an open trench with a standard iPhone Pro — no specialist scanning hardware and no separate surveying appointment
- Centimetre-accurate point clouds: Reconstruction algorithms developed at ETH Zurich build a high-resolution 3D point cloud of the excavation from the video alone
- Standards-compliant CAD output: Generates as-built plans in DWG and DXF, with couplings and pipe runs identified and measurements simplified
- 3D digital twin and GIS export: Produces a model of the pipe route including building entries that drops into existing GIS systems
- Works without GPS: Captures basement sections and building entry points where GNSS-based surveying fails
- Immediate backfilling: Because capture takes minutes, trenches close right after filming instead of waiting on a survey crew
- Documentation in about 72 hours: Complete records arrive weeks earlier than conventional surveying, enabling prompt connection billing
- Third-party utility capture: Records crossing utilities and as-laid geometry as unbroken 3D evidence, replacing hand sketches
Best for
- A utility network operator documenting residential service connections without booking a surveyor for every site
- A contractor closing a trench the same day instead of leaving it open pending a survey appointment
- Capturing a building entry point in a basement where GPS-based surveying cannot get a fix
- A district heating project producing as-built DWG plans for regulatory sign-off
- Spotting a laying error in the 3D point cloud before backfilling, while the fix is still cheap
- Feeding as-built pipe geometry into a GIS system for long-term network maintenance planning