
Space visuals and proposals for real estate
Reads layout and scale from photos of vacant space, generates design options in several styles, and assembles the proposal around client survey results.
Proposals in days, not 2–4 weeks
- Customer
- CBRE
- Areas
- Visualization
- Deployment
- PoC

1Problem
Pitching an empty commercial space meant building a design, interior concepts and a budget from scratch for every tenant. Outsourced visuals typically took five or six rounds of revisions to match intent.
2Input
Tenant survey (headcount, shared space, location, hours of use, design preferences) and photos of the empty space
3How it works
The model extracts structure and scale from the listing photos, generates several styles with a virtual renovation model, and writes the proposal together with the survey analysis.
4Output
Three style options for an empty office, and proposal pages with area tables
Results
- Proposals in days, not 2–4 weeks
- A key reference for entering the North American market
Could this work on your projects?
Tell us about your challenges, and we'll explain how a similar approach could apply.
More case studies

On-premises rendering for industrial plants
Scattered design data, restructured so AI can use it. Fine-tuned models and section-level prompts run as a lightweight deployment on the client's own infrastructure.
Phase 1 live, now in support and maintenance

Landscape options from site plans
Select an area on an early landscape plan and describe what you want. A model trained on Korean residential landscapes generates the options.
4 landscape options per area, in one pass


RFI answers for structural review
RFIs, structural drawings, and site photos, structured into one knowledge base. It finds similar past cases and drafts answers that cite the governing code clauses.
Draft RFI answers from similar past cases
