ScanTo3D | OpalAi vs 3DFY.ai

ScanTo3D by OpalAi is a 3D generation app for iPhone Pro and iPad Pro that turns LiDAR walkthrough scans into floor plans, point clouds, and BIM-ready models. You walk through a space with your phone, capture geometry in InstaCAD or LiDAR mode, and export digital twins in formats like OBJ, GLTF, STL, and USDZ. It targets property owners, contractors, and facility teams who need as-built documentation without hauling a dedicated scanner.

Compared to renting tripod LiDAR hardware, ScanTo3D trades equipment cost for device requirements and optional cloud processing. InstaCAD mode builds 2D floor plans and 3D CAD models in real time for spaces under 2,000 square feet, while LiDAR mode handles larger environments with no hard size cap though OpalAi recommends keeping each scan under about 5,000 square feet.

Site managers, real estate teams, and construction sales staff use it for quick floor plans, ANSI-compliant gross living area calculations, and textured 3D exports. OpalAi claims less than 1 inch of error per 30 feet and about 98% accuracy on generated floor plans and BIM objects.

3DFY.ai revolutionizes the process of 3D model creation by leveraging the power of artificial intelligence. This innovative platform allows users to generate highly detailed 3D models with ease, using either a simple text prompt or a single image as the starting point. The technology is designed to cater to a wide range of industries and individual creatives, providing a scalable solution for high-quality 3D asset production. 3DFY.ai offers various services, including 3DFY Prompt, Megapacks, Image processing, and custom solutions that meet the specific needs of businesses and creators. With 3DFY.ai, producing 3D content is no longer confined by traditional methods like photogrammetry, 3D scanning, and manual creation, which are often costly, time-intensive, and difficult to scale up. This platform is perfect for those seeking to express themselves in the 3D space or businesses aiming to generate massive 3D datasets swiftly and efficiently.