VirtualSpaces:Turn Messy 2D Floor Plans into Reliable 3D Spaces

Most real estate, architecture, and design workflows still revolve around a single artifact: the 2D floor plan. It’s dense, technical, and unforgiving and yet it’s the only window into a space for most buyers, tenants, and even internal stakeholders. 

VirtualSpaces exists because we believe that’s no longer good enough.

VirtualSpaces is an AI-native engine that takes raw 2D floor plans: Floor plan images and converts them into structured, reliable 3D-ready data. Instead of throwing generic computer vision and OCR at the problem, we treat floor plans as a specialized document language. Our models are trained to understand architectural conventions, symbols, and room semantics, then map them into a coherent spatial model that a 3D engine or design tool can work with.

What does that unlock?

• For proptech and real estate teams: Instant, accurate 3D layouts from plan sets you already have, enabling better pre-sales experiences, remote walkthroughs, and consistent marketing assets without waiting weeks for manual modeling.

• For architects and designers: A way to bridge from technical drawings to design explorations and virtual staging in minutes, keeping you in the loop instead of replacing your expertise.

• For AI experts and computer vision engineers: A real-world domain where document understanding, spatial reasoning, and generative visualization intersect in a way that actually impacts how people make high-stakes decisions about space.

We’re not another “virtual staging” app with a few templates and filters on top of generic renders. VirtualSpaces is built as an underlying capability that can sit behind your product, workflow, or platform. Give us your floor plans, and we give you back a structured representation of the space plus the tools to visualize, furnish, and iterate on it at scale.

If you work in proptech, architecture, interior design, or you’re building tools that touch any part of that stack, we’d love your feedback. How are you handling 2D-to-3D today? Where are the bottlenecks, the manual hacks, the “we just live with it” compromises?

Check out VirtualSpaces, play with what we’re building, and tell us what would make this a must-have capability inside your product. This is a hard, messy problem, but it’s exactly the kind of problem the next wave of AI and computer vision should be solving.

Read More: Why parsing a document to generate 3D is an incredible hard problem to solve

Cheers!