AppRoast

AppRoast

Discover why users hate (or love) any app

GregStefaniak
@GregStefaniak
Last updated on May 19, 2026
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Freemium
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How AI and people discover AppRoast on PeerPush

Read by AI engines 30dEngines readingHow many times AI crawlers read this listing, and which engines those crawlers belong to.
127
  • Perplexity
  • Claude
  • ChatGPT
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PersistenceRead streakConsecutive days, counting back from today, that AI has read this listing every single day.
24 days

Read by AI every day

Read by AI every day for the last 24 days.
Search index 90dSearch indexTimes a search engine AI indexer, such as OAI-SearchBot, crawled this listing.
27 crawls

ChatGPT Search indexer

By OAI-SearchBot, the ChatGPT Search indexer, in the last 90 days.

About AppRoast

I got tired of manually reading app reviews, so I built AppRoast. While validating product ideas, I kept running into the same problem: Understanding *why* users are unhappy means digging through hundreds of repetitive App Store and Google Play reviews. - Across iOS and Android. - For your app. - And competitors. - It gets painful fast. So I built **AppRoast**. Paste any app and get an instant AI-powered roast based on real App Store & Google Play reviews. Right now AppRoast helps surface: 🔥 Top complaints users keep repeating 😍 What users actually love ⚡ Quick wins for developers 📱 iOS vs Android differences 📊 Real sentiment from ratings & reviews Works for your own app. Works for competitors too 👀 **Honest MVP note:** I’m launching early to validate demand before building the full platform. Roasts currently analyze a focused set of recent reviews to keep things fast (and free), while still surfacing strong patterns quickly. The bigger vision: → deeper historical analysis (up to 5,000 reviews) → monitoring & sentiment alerts → competitor tracking → PDF reports → roast history & comparisons I’d genuinely love founder feedback: **Would you actually use something like this?** And more importantly: **What would make this valuable enough to pay for?** AppRoast → approast.app

Product Video

Watch a video demo of AppRoast.

Screenshots

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Product Updates (1)

GregStefaniak
@GregStefaniak

Day 1 of launch 🚀

Here’s what the most checked apps look like after the first day of APPROAST. 📊 Most Checked Apps (based on 96 total app checks) TikTok — 15% Uber — 13% WhatsApp — 12% Instagram — 10% Facebook — 9% ChatGPT — 8% Spotify — 8% YouTube — 7% Discord — 6% Duolingo — 5% Interesting start 👀 BTW: what do you think about adding real-time stats to the site with filters for day / week / month / all-time? Would you actually use it?

Product had at the time: 12 upvotes • 5 comments • 6 followers • 25 PeerPush

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Reviews (3)

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Based on 3 reviews

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ralphmatysiak

Cool concept. My only question is retention — I can see myself using this heavily during launch or when iterating on onboarding, but maybe not daily. That said, competitor analysis feels like the hidden gem here. Being able to quickly see why users hate competing apps is genuinely valuable. Congrats and good luck with the launch 🚀

Comments (4)

budrys
@budrys

Interesting positioning. Most review analytics tools tell you what users said. This seems more focused on why users are frustrated and what to actually do next. Curious — are you planning monitoring/alerts?

garethstone81
@garethstone81

This scratches a very real itch. Reading app reviews manually is one of those things everyone knows they should do, but nobody actually has time for. I like that you turned it into something opinionated instead of another generic “AI senti

GregStefaniak
@GregStefaniak

Built AppRoast because manually reading App Store & Google Play reviews is miserable 😅 Honest MVP — would you actually use AI-powered app review roasting? What feature matters most?