Site-to-Massing Studies
Generate concept massing options from parcel boundaries, setbacks, height envelopes, FAR targets, orientation, and simple program ratios.
Experimental design intelligence
Architecture AI
X Lab
A private research environment for early-stage architectural decision-making: site interpretation, massing studies, program test-fits, climate checks, and design-option comparison before a project moves into detailed BIM or documentation.
Research modules for the front end of architectural design.
X Lab focuses on feasibility and concept design, where teams need to compare imperfect options quickly without losing traceability of area, constraints, and design assumptions.
Climate & Daylight Checks
Estimate solar exposure, overshadowing risk, daylight access, and wind-sensitive edges early enough to influence the basic form of the project.
Facade System Exploration
Explore facade rhythms, window-to-wall logic, shading depth, material tone, and contextual references while keeping the result tied to massing geometry.
Program Test-Fit Reasoning
Suggest adjacency patterns, circulation strategies, lobby placement, core options, and preliminary unit or workplace planning assumptions.
Material & Atmosphere Notes
Translate design intent into material palettes, envelope concepts, interior atmosphere, and reference language that can guide visualization or documentation.
Urban Context Reading
Summarize surrounding height, street hierarchy, arrival points, pedestrian edges, view corridors, and likely pressure from adjacent uses.
Designed for architectural evidence, not generic image generation.
The prototype treats a design option as a bundle of constraints, drawings, assumptions, and review notes rather than only a rendered image.
What the lab reads
- Site dimensions, setbacks, height limits, and orientation.
- Program targets such as GFA, unit mix, amenity ratio, or workplace density.
- Design intent, reference images, planning notes, and review comments.
What it produces
- Comparable concept options with area and planning assumptions attached.
- Early risk notes for daylight, exposure, circulation, and contextual fit.
- Briefing text, diagram prompts, and next-step questions for the team.
What remains human
- Architectural authorship, spatial judgment, and final design selection.
- Local code interpretation, consultant validation, and authority submissions.
- Client strategy, cost decisions, procurement, and construction coordination.
Design method
From brief fragments to comparable design evidence.
The lab is structured around architectural review cycles, not one-click final answers. Each option should expose the brief, assumptions, spatial consequences, and known uncertainty.
4review checkpoints
6research modules
H2web-first delivery
Alphaprivate preview
01
Structure the brief
Capture site facts, program targets, planning constraints, performance goals, and the design question being tested.
02
Build option families
Generate several massing and planning directions with traceable assumptions instead of a single opaque proposal.
03
Run concept checks
Compare area yield, daylight access, envelope exposure, circulation clarity, contextual fit, and unresolved risks.
04
Prepare design rationale
Convert the selected direction into review notes, diagrams, comparison tables, and next-step questions for the design team.
Research preview
Private alpha for architectural research and early feasibility work.
Architecture AI X Lab is not a public SaaS product. It is a controlled research preview for testing how language models, geometric reasoning, environmental signals, and design review workflows can support architects without replacing professional judgment, local code review, or consultant coordination.