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Build-to-Rent Studio

Six chapters take one site from planning envelope to stabilised asset, and every decision moves real numbers. Generate and score four massing typologies inside the envelope, cut genuine floorplates with a sized core and a double-loaded corridor to your unit mix, panelise every facade into a repeating DfMA kit, then watch the tower rise in 4D against a floor cycle you control. The final chapter is the pro forma: rent roll, cost plan, yield on cost, stabilised value and a sensitivity tornado. Commit each chapter and the studio writes a decision ledger, then hands you an investor board pack and AI-rendered visuals.

Published

What this demonstrates

Generative BTR feasibility + DfMA delivery intelligence. The same generative feasibility, DfMA panelisation and 4D programming architecture we build for build-to-rent developers and institutional investors, encoded here with distilled Melbourne benchmark assumptions.

Units
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Res net-to-gross
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Panel repetition
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Programme
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Yield on cost
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Each headline number unlocks when its chapter is committed. Benchmark assumptions, editable throughout.

Chapter 1 · Site & Envelope
Where are we building, and what will planning allow?

Goal seek unlocks once the massing chapter commits: state a business goal and the engine redesigns the scheme toward it, live in the viewer.

Chapter 1 of 6

Site & Envelope

Where are we building, and what will planning allow?

Choose the site

Three benchmarked sites, or dial in a custom parcel below.

Site preset

Docklands waterfront sits on a harbour-edge promenade with tram access and open water outlook.

Planning envelope

What planning allows on this parcel, before a single wall is drawn.

Height limit110 m
Podium max height20 m
Tower plate cap950 m²
Site coverage cap80%
Street setback
4 m
Side setback
4.5 m
Rear setback
6 m
Tower setback
3 m
Buildable W
53 m
Buildable D
40 m

Site dimensions

Boundary dimensions the massing engine builds inside.

Width (W)62 m
Depth (D)50 m

Land cost

Acquisition cost feeds the pro forma in the final chapter.

Land cost$38.0m

Demonstration only. Yields, costs, programmes and returns are indicative benchmark assumptions and should not be relied upon for investment, planning, regulatory or construction decisions. Professional review is required.

Apartment Design Guidelines for Victoria

Where this data comes from

Illustrative pipeline for a production deployment

Planning envelope datasets

Height limits, setbacks, podium controls, floorplate caps and site coverage, encoded per site as a machine-readable envelope

Cost benchmark libraries

Rates per square metre of GFA by element group, prefabrication adjustments, escalation and holding costs

Unit standards

Build-to-rent unit modules with net areas, frontages, core sizing rules and amenity provision targets

DfMA panel families

Unitised facade module grid, panel family definitions, craneable weight classes and factory production rates

Generative BTR engine

  1. 1Generate and score four massing typologies inside the envelope
  2. 2Cut real floorplates: core, corridor and units to the mix target
  3. 3Panelise every facade into a DfMA kit and count unique types
  4. 4Build the 4D delivery programme from the resulting quantities
  5. 5Run the pro forma: cost plan, rent roll, yield on cost, sensitivity

Output

Investor board pack

Decision ledger, massing comparison, floorplate drawings, facade panel schedule, delivery programme, pro forma and 3D captures assembled from one parametric model

This browser demo runs distilled benchmark assumptions; client deployments encode the actual planning controls, cost plan and unit standards for the real project and land results in Revit, IFC or the client's own platform.

FAQ

Frequently asked questions

How these demos relate to the systems we build for clients.

What does this studio actually demonstrate?

One parametric model carrying a whole build-to-rent development, chapter by chapter. The engine generates four massing typologies inside the planning envelope and scores each for GFA, unit yield, facade area, cost index, solar access and wind exposure. The chosen form is then cut into real floorplates with a lift core sized from the units above it, two fire stairs, a 1.8 m double-loaded corridor and units placed to a mix target. Facades panelise into a unitised kit, quantities drive a 4D delivery programme, and the pro forma closes the loop. Nothing is pre-baked: change the height limit in chapter one and the yield on cost in chapter six moves.

How is yield on cost computed here?

Bottom up, from the geometry. The cost plan applies rates per square metre of GFA by element group (structure, facade, services, fitout) to the quantities the engine produced, adds preliminaries and escalation, and adds land, so total development cost is a consequence of the design rather than an input. Income is a rent roll built from the actual units cut on each plate at weekly rents by type, adjusted for the site, plus car parking and storage income, less vacancy and an operating expense ratio. Stabilised net operating income divided by total development cost gives yield on cost, and the sensitivity view swings rent, cost, programme and cap rate to show which one the return really depends on.

What does DfMA panel repetition mean for delivery?

Repetition is what makes a facade a manufactured product instead of a construction activity. The studio panelises every elevation onto a 1.5 m module at 3.3 m floor to floor, assigns each bay a family (glazed, solid insulated, balcony or corner), then counts how few unique panel types deliver the whole building. High repetition means one panel is drawn, prototyped and tested once, then produced hundreds of times at a steady factory rate while the structure is still rising. In the programme chapter that shows up directly: unitised facade and bathroom pods compress the facade and fitout durations against the stick-built comparison, and the studio reports the weeks saved and what each week is worth.

How would this deploy into a client BIM ecosystem?

As an engine, not a website. The geometry, plates, panel schedule, programme and cost model are pure functions over a single configuration object, so the same code can drive a Revit or IFC exchange, publish quantities to a cost system, push panel families to a fabricator, or feed programme data to a scheduling tool. In client work we replace the distilled benchmark assumptions with the project's own planning controls, unit standards, cost plan and supplier rates, connect it to the live model and data environment, and land the results as native model elements and reports rather than screenshots.

Want this for your products?

Everything in the Playground is built with the same stack we deploy for clients: configurators driven by real product masters, planners connected to BIM data, and AR experiences served straight from the product catalogue.

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