Maket Launches Move Rooms: Don't Redraw the Entire Floor Plan Just to Adjust Layouts
AI-powered residential design tool Maket has released Move Rooms, which turns rearranging rooms into a native floor plan editing action. It is built to solve the unnecessary high costs that pile up after the third round of design revisions.
According to coverage by Nero Soares, author at TestingCatalog, Maket has launched the Move Rooms feature dedicated to floor plan editing. Targeting residential design use cases, Maket leverages AI to generate floor plans and renderings. The core selling point of Move Rooms is very straightforward: you can move rooms directly on an existing floor plan, the system will automatically process all associated geometric relationships, so users never have to scrap the current draft and redraw from scratch.
For ordinary users, this works just like dragging blocks on a canvas. For the full design workflow, its greatest value lies in early-stage design comparison. Most home layout adjustments are minor tweaks: shifting the living room half a meter, swapping the bedroom position, or switching the kitchen and dining area, but even small changes can trigger cascading adjustments across the entire floor plan. While regenerating a new version with AI is fast, the output often fails to retain all your previous custom edits. Move Rooms puts direct editing control back in users' hands.
Our assessment: The competition for qualified first-version generative design outputs is already extremely saturated. The factor that truly impacts real-world usability is revision cost. Whether a tool can stay integrated into a team's regular workflow depends on if it can hold up even after the 10th round of adjustments. Move Rooms directly addresses this key pain point.
Hands-on experience is still required to confirm unaddressed details: what types of projects are supported, whether dimension labels, doors and windows update automatically after moving rooms, how the tool indicates structural walls and load-bearing limits, as well as available export formats and pricing tiers. Public reports do not elaborate on these details, so do not mistake the public demo for full production-grade functionality.
For developers, this feature also serves as a clear reminder: the interaction layer of an AI product often determines user retention far more than model parameters do.
Original Source: TestingCatalog
发布时间: 2026-10-31 02:30