Alquilame.io

TrustMRR

Lightweight rental management platform that helps small businesses organize their products, reservations, and clients. It lets users create a public catalog, manage bookings, and communicate directly

Lightweight rental management platform that helps small businesses organize their products, reservations, and clients. It lets users create a public catalog, manage bookings, and communicate directly through WhatsApp — no commissions, no complicated setup.

Visit product View on TrustMRRSep 25, 2025SaaS Rental B2B

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Actual performance

12customers

$129MRR/mo

Did not reach leaderboard

Traction signals

Domain Rating28

MRR growth 30d-62.9%

Launch Intel predictions

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TrustMRRFits verified-revenue profile · Strong signals: users · Missing: mobile apps, ios, personal

67%67% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

54%54% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: platform, users · Missing: plus, intuitive, reviews

40%40% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

36%36% predicted probability of success on Hacker News, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: user · Missing: mac, agents, macos

36%36% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

19%19% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

15%15% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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