RentIQ
An AI rent & revenue-management platform that recommends the optimal rent for every multifamily unit from demand, comps, seasonality and exposure — and guides each renewal offer.
// The Revenue Management board — portfolio KPIs, a 12-month effective-rent trend rising to $1,842, and a floor-plan pricing table with AI-recommended rents.
Figures from the engagement, shared under NDA.
We publish them unchanged and can’t break them down any further here. The reference build you can open runs entirely on sample data.
If you read one part of this page, read these 4 lines.
- Recommends the revenue-optimal rent for every floor plan, not a single blanket number
- Every price is explainable — attributed to weighted demand, comp, seasonality and exposure drivers
- Guides each renewal offer against move-out risk with a projected acceptance rate
- One portfolio view of effective rent, occupancy and revenue-vs-budget for revenue leadership
What it does — and which part of it we built.
RentIQ gives multifamily revenue managers a pricing brain for the whole portfolio.
It scores demand for every floor plan, plots a demand curve to locate the revenue-optimal rent, and attributes each recommendation to weighted drivers — demand strength, comp position, seasonality and exposure — so the number arrives with the reasons behind it. BuildspaceLabs designed and built the MVP front end: a Revenue Management board for portfolio-wide pricing and a per-floor-plan detail view with a rent-recommendation card, a comp set, an inline demand curve and a renewal-offer builder — turning a demand model and a stream of market signals into prices a revenue manager can publish in minutes.
Every screen here is from the reference build, not the client’s system.
The captions say what you are looking at. Every name and record on them is sample data.
What the engagement left the client with.
- Delivered a production-quality MVP of the Revenue Management board and floor-plan pricing detail in a 9-week engagement
- Consolidated unit pricing, comp intelligence and renewal offers into a single revenue-manager workflow
- Gave revenue leadership a real-time view of effective rent, occupancy and revenue-vs-budget across 1,240 units
- Established a reusable design system (pricing curves, driver bars, recommendation cards) for the product's next surfaces
The stack was picked per constraint, not per house habit.
7 technologies across 4 layers — the shape of the stack follows the problem.
Every feature in the build (6)
- Revenue Management board with effective-rent, occupancy and revenue-vs-budget KPIs
- Unit-level pricing table with AI-recommended rents, change %, demand score and days on market
- Demand curves that plot projected lease-up against rent to locate the revenue-optimal price
- Driver attribution across demand strength, comp position, seasonality and exposure & vacancy
- Comp intelligence — nearby properties tracked by distance and effective rent
- Renewal-offer builder weighing move-out risk with a projected acceptance rate per offer
Don’t take our word for it — it is running in the frame below.
This is the same page the provenance block links to: our reference build for RentIQ, with its own look, copy and motion. Scroll inside it, or open it full-screen.
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