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Applications and systemsAutomation3D visualisation

Sales and after-sales system for a developer, with 3D walkthroughs built from floor plans

Client: Residential developer, three developmentsIndustry: Real estate17 October 2026
Results
flats with their own 360° walkthrough
81 of 82
3D scenes generated from floor plans
37
render cost of one scene after optimisation
1.35 USD

Challenge

The sales team prepared offers by hand, as plain text, and did not know whether the client had opened them at all. Defects reported after handover need a response within the statutory 14 days, and the only reminder was a calendar. Complaints arrived by email and many of them concerned ordinary wear and use, which tied up the team.

A client buying a flat saw only the floor plan. Commissioning a visualisation of every interior separately would have cost a lot and taken weeks, and the offer included 199 flats across three developments.

Approach

All tools read flat data live from the developer’s content system, so a price or status changes in one place. An offer is produced as a PDF and an online page with open tracking and an interest button, and each one enters a funnel: sent, opened, interested, reservation, sold.

For complaints we deliberately added a controlled entry threshold. A short phone line collects consents and the category, filters out wear-and-use cases and sends an SMS with a link to a form with a checklist and photos. We decided to generate the 360° walkthroughs from code: scenes are created automatically from the flat records, and rendering runs in a GPU cloud.

Implementation

The defects dashboard sends reminders 7 and 2 days before the deadline and after it has passed, each exactly once. The defects and complaints dashboards share a login and a task board with change history. The phone line runs on conversation state stored in the database and verifies the signature of every call from the carrier.

The walkthroughs use high-resolution panoramas in AVIF (4 panoramas take 2.2 MB instead of 6.5 MB in JPEG), a kiosk mode with a QR code for trade fairs and buttons on the developer’s website. The build blocks publication if the area on the floor plan does not match the flat record. We checked 308 labels this way.

Results

81 of 82 flats have their own walkthrough. One sold unit with a unique floor plan is missing. The 37 scenes came from 21 floor plan families, 13 variants and 3 additional scenes. Units with the same layout use reference panoramas.

Render optimisation reduced the cost of a scene from about 2.50 to about 1.35 USD. The engine now works outside this project: a new scene takes about 24 minutes of machine time for about 1 USD. The walkthroughs were ready before the housing trade fair in October 2026.

How it is built

Data integration
A WordPress plugin (mu-plugin) exposes apartment data from ACF fields. The offer generator, panels and walkthroughs read it live, so there is no second copy of the offer that could drift out of sync.
Offers
Next.js and PostgreSQL. PDF rendered from HTML in Puppeteer, apartment sheet appended with pdf-lib, and an online version with open tracking. Images are fetched only from an allowlist of hosts.
Defects and complaints
Two systems with a single sign-on: SSO on a shared domain, with section access carried in a signed token. Reminders are idempotent thanks to an event log and a unique index in the database.
Hotline
Twilio Voice with Polish speech synthesis, call state stored in the database for every call, signature verification on every request, an SMS with a link, and a daily message limit per number.
3D walkthroughs
Blender scenes generated from Python code based on apartment sheets, GPU rendering in the cloud (Modal), 6144×3072 panoramas in AVIF, and the Photo Sphere Viewer. The static service behind nginx uses about 6 MiB of RAM.
Checks
The build rejects a floor area label that does not match the apartment sheet. Tests in the WebKit engine reproduce iPhone behaviour, and kiosk mode runs from a QR code at trade fairs.

Technologies

  • Next.js
  • PostgreSQL
  • WordPress
  • Puppeteer
  • Twilio
  • Python
  • Blender
  • Modal (GPU)
  • Cloudflare R2
  • Kubernetes
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