3DnAt AI 3D Scanning Solutions converts images, videos, and real-world objects into hyper-accurate 3D models using AI technology. This enables businesses in e-commerce, gaming, healthcare, and VR to visualize, design, and innovate with interactive 3D products and immersive environments.
Funding
Funding not disclosed
Founders
Product
Problem
Creating accurate 3D models from images, videos, or text prompts can be a time-consuming and technically challenging process, often requiring specialized software and expertise. Businesses across various sectors struggle to efficiently generate high-quality 3D assets for e-commerce, gaming, healthcare, and other applications. This bottleneck hinders innovation and limits the potential for immersive experiences and interactive product visualizations.
Solution
3DnAt AI 3D Scanning Solutions offers an AI-powered platform that simplifies the creation of hyper-accurate 3D models from various inputs. The platform supports image-to-3D, video-to-3D, and prompt-to-3D conversion, enabling users to generate 3D assets in seconds. Its B2B solution integrates seamlessly via API for web, mobile, and desktop platforms, while its B2C solution offers a user-friendly experience on Android and iOS devices. The generated 3D models can be exported for use in e-commerce, gaming, construction rendering, healthcare, and virtual try-on applications.
Target Audience
The primary target audience includes businesses in e-commerce, gaming, construction rendering, and healthcare, as well as individual users seeking advanced 3D capabilities on their mobile devices.
Features
- AI-powered 3D model generation from images, videos, and text prompts
- API integration for web, mobile, and desktop platforms (B2B)
- Mobile application for Android and iOS (B2C)
- Scalable 3D model creation for architectural visualization
- Support for virtual try-on applications in e-commerce
- Compatibility with gaming engines for creating lifelike assets and dynamic worlds
- 3D scanning for prosthetics, surgical planning, and patient-specific modeling in healthcare