Portfolio Pricing
Pranay Gaurav
Portfolio Pricing fixes the self-competition blind spot in single-listing engines by auditing your whole book for markets where your own homes collide, recommending which to hold or clear.
Hackathon Projects
Rabsh
Chisom Elvin
Rabsh lets rental owners test pricing strategies risk-free instead of guessing: 9 strategies simulated through Wheelhouse's real pricing engine, ranked by projected 90-day revenue, winner applied in one click.
Minimum Rate Impact Model
Joel Arteaga
Combines WH data with Revnest's Rent Potential Engine to show when a listing's min rate is protecting revenue versus restricting demand; recommends a smarter floor backed by projected revenue impact and affected nights.
Helm
Mannas Narang
2 AI agents on top of live WH data—Warden triages underperforming units and fixes or flags them with human approval, while Beacon drafts ready-to-run demand campaigns for correctly-priced units that still aren't booking
Night Margin
Mikael Lehtonen
Flag nights priced below their cost floor (finding 206 such nights on one portfolio), then lets you draft, preview, apply, and revert corrected floor prices back to Wheelhouse
RevTune
Quinn Hubertz
Asks a quick 3-question check after each booking to surface patterns in your pricing feedback, turns them into 1-click WH strategy changes, and cross-checks your gut against neighborhood fill-rate data
HELM
Maria Lancaster
A revenue dashboard for a 104-door Amelia Island STR portfolio, built on live WH data, with Executive and Revenue Management views covering performance, pacing, availability, P&L, and What-If scenario modeling
Price Pulse
Farzad Ehtemam
Understanding parts of the portfolio that are out-of-sync with market prices and finding opportunities for future growth
Haystack
Emily Pattillo & Sarah Franzen
Haystack, part of RevzenOS, nightly monitors the overlooked "quiet middle" listings that leak money at scale, surfacing pricing issues using portfolio-specific SOPs built on a decade of operational experience.
CompSnoop
Rashard Hinds
Automates daily competitor research by shopping the market like a guest across channels, evaluating price, amenities, reviews, and availability to flag when you're not the best value, then recommends the smallest fix
Revbnb
Purushottam Deshpande
RM that uses nine specialized AI agents to automate analysis, pricing decisions, and repetitive tasks—learning from outcomes to continuously improve—across portfolios from a single listing to 1,000+ properties.
The Book
Ben Coleman & Mylen Adan
This tool surfaces homeowners who need proactive outreach, guides RMs through YoY talking points, and maintains a homeowner profile tracking call transcripts, promises made, and performance alerts across a multi-user system.
Revy
Henry Corell & Travis Puckett
A revenue analyst agent trained on coded "skills" rather than raw LLM judgment—grounded in beating YoY booked ADR, beating the market via Wheelhouse/Revnest data, and incorporating additional context
Homeowner Acquisition Rental Estimator
Jonathan Fonvielle
Gives potential homeowners an opportunity to see what revenue their house might make in our rental program; captures prospect contact info, offers them a chance to book a meeting with me and kicks off messaging
LeverLab
Alex Tran
(Sorta) know if your pricing change worked. Market-normalized evidence in under 2 minutes.
Project Reins
Jeff Brown & IntelliHost
Monitor listings using WH RM comp-set data to surface only the moments that matter, with the dollar impact and fix; approve real pricing decisions with one tap instead of babysitting dashboards or ceding control to a black box.
Revenue Atlas
Michelle Byrd
A decision-and-execution layer that scores and explains revenue opportunities from WH and reservation data, letting operators act on ranked, confidence-gated recs while a shared state tracks the modeled financial impact in real time.
DARE Just Say No
Ben Coleman & Mylen Adan
Trace rate history against booking-window search data to price aggressively or conservatively, segments guests into 150 cohorts for targeted email campaigns, and free-query by KPI to segment and push pricing directly into WH
RateScope
Dustin Sons
Comparing owned properties against market trends at a glance.
Forecasting Simulated Setting Changes
Jordan Locke
This Prometheus revenue play uses WH data to infer demand, simulates bookings across the real calendar (including cancellations), and combines that with setting-change price previews to estimate a range of KPIs.
Swipr
Jonathan Fonvielle
Swipe 5 cards every morning to automate optimizing empty nights at your homes. It uses your listing data, booking pacing and market data to give you the 5 best opportunities edit your listing, pricing and reservation strategies.
Zeppelin Flightplan
Rudolf Nanne
Reconstructs a listing's minimum-stay logic day-by-day (matching live calendars 365/365), explains how settings interact across the year, and previews recommended changes
Gap Rescue Radar
Deng Aguer Bul
Scans 180 days of WH data to find unbooked night gaps, diagnoses if the cause is min-stay rules, booking patterns, lead time, or pricing, and recommends transparent, operator-controlled fixes rather than defaulting to a discount.
Helm
Shaik Huzaifa
Turns WH portfolio data into one ranked, explainable worklist per property—merging revenue recommendations with operational tasks
Nocturne
Jason Lopez
Nocturne is a loyalty and exchange network where independent vacation rental owners convert unsold nights into "Moons," a travel currency redeemable for stays across the network—giving PMs selling point with owners.
Revenue Central
Alisa Kück & Curated Property
A centralized RM platform for analyzing property and portfolio performance, reservations, and pacing; generating owner reports and forecasts; tuning pricing algorithm settings; and using AI to push changes directly to WH.
Gravity
Jonathan Fonvielle
Models your portfolio as a live gravitational field, showing how strongly each listing pulls demand from competitors and surfacing the smallest price moves that increase that pull without sparking a race to the bottom.
Reeve
Michel Lopez
Unifies pricing and operational context across every managed home, surfacing key decisions, proposing strategies, and delivering daily Slack briefs and on-demand dashboards
BookBy.Date
Victor Kane
BookBy connects the systems and learns when each date should book, watches the exact stays still available, and uses WH and Guesty to raise, hold, lower, or protect them. Then it confirms the result.
Richer Agenda
Aaron Calloway & Heather Richer
This tool creates a visual, streamlined method to detect anomalies in performance, establish watchlist protocol, and communicate and execute actions all in one place.
Morning Triage
Doug Truitt & Rachel Robinson
Morning Triage uses WH's RM API to review every listing overnight, so revenue managers wake up to only the ones needing a real decision—with the numbers, one-click actions, and remembered reasoning attached.
Horizon
Mannas Narang
With a prospective owner's address, it builds a data-backed earnings proposal that you can email on the spot. For current owners, it auto-generates monthly reports on earnings versus the market.
Pricing MRI
Parker Place
Combines WH settings and booking history with calendar data from BNBCalc's Visual Comp Selector to help RMs spot mispriced settings, benchmark against real competitors, and preview changes before pushing them to WH
Revenue Intelligence & Action Centre
Samruddhi Waghchaure
The application gives a portfolio-level view of pricing, reservations, and OTA performance. It combines Wheelhouse, budget, and AI-based impact analysis to surface insights and create a path from performance issue to action.
AskRichardVaughton
Otamiser
Gives owner relations teams instant, data-backed answers on revenue impact and pushes owner feedback straight back into WH pricing, eliminating bottleneck so owner relations can focus on the relationship, not the numbers.
RevTrace
Chisom Elvin
RevTrace helps short-term rental operators spot underpriced or overpriced dates by comparing live calendar rates with Wheelhouse recommendations and explaining the biggest pricing gaps.
Kivora
Olamilekan Lapite & Samuel Adesugba
Kivora is an AI revenue-ops workflow that detects pricing incidents and opportunities in live STR portfolio data, explains its evidence, requires approval before any live pricing action, then verifies outcomes and measures impact
ACME Rate Explainer
Patrick Gerzanics & Filip Kostic
This tool helps revenue managers quickly explain rate calculations to owners by showing base rates and date-range pricing decisions alongside an LLM-generated explainer they can use as talking points.