Dwellable – The app I built after waiving home inspection during Covid

Hacker News

When my wife and I bought our first home in 2020, it was peak COVID. Our agent actually asked us to waive the home inspection, which was terrifying. I ended up walking through the house myself with a set of handwritten notes: “check if Kitchen outlets are GFI,” “make sure toilet flushes”, “test the bath fan”, etc. That experience became the seed for Dwellable, a home maintenance and inspection app for homeowners like us who didn’t know where to start (both before and after buying). The app automatically pulls your property records (square footage, year built, fuel type, etc.) and uses AI to recommend reminders and seasonal maintenance tasks. It’s free right now, built entirely native on iOS and Android. On the side, I’ve been experimenting with VLMs (vision language models) to analyze photos that users take during inspections, for things like spotting corrosion or damaged caulking. If you’ve ever felt lost after closing on a house, this might resonate. Tech stack: - Backend: Python + gRPC, RabbitMQ - AI: Perplexity + OpenAI - iOS: SwiftUI - Android: Fully compose Would love feedback!

Visit product View on Hacker NewsOct 31, 2025

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Product HuntOn track for Day 1 leaderboard · Strong signals: agent, model, user · Missing: mac, agents, macos

81%81% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

77%77% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

61%61% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

32%32% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

30%30% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

21%21% 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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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