AI-powered local SEO platform that helps businesses rank higher and generate more customers.

Acquire.com

This AI-powered local SEO platform helps service businesses rank higher and win more customers. It unifies rank tracking, citations, profile updates, and customer engagement into one simple workflow.

This AI-powered local SEO platform helps service businesses rank higher and win more customers. It unifies rank tracking, citations, profile updates, and customer engagement into one simple workflow. Built for agencies and multi-location brands, it automates reporting and includes a verified local contact database to find and message high-intent prospects—delivering clear ROI with minimal effort. Key Highlights ✅ 500–999 paying customers; bootstrapped B2B SaaS ✅ $540,878 ARR; TTM $431,473 r...

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Actual performance

$45,073/yr

Made the leaderboard

Traction signals

Asking price$1,500,000

Annual revenue$540,878

Revenue multiple2.8x

Launch Intel predictions

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

87%87% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Acquire.comFits revenue-generating acquisition profile · Strong signals: arr, saas, ttm · Missing: mrr, revenue, profit

68%68% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

51%51% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

44%44% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

29%29% predicted probability of success on Product Hunt, 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

16%16% predicted probability of success on Hacker News, based on ML models trained on real launch data.

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

8%8% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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