AI-powered LinkedIn automation tool for agencies and sales teams to find leads and book meetings.

Acquire.com

This AI-powered LinkedIn outreach platform helps agencies and sales teams find leads and book more meetings with true 1:1 personalization. Bootstrapped and profitable, it grew from $0 to $56K MRR in five months on sticky, recurring revenue. Built for multi-account workflows, it makes managing many client seats simple while lifting reply rates with enrichment, voice notes, and smart sending. With ~$800K TTM revenue and 50%+ margins, it’s a turnkey, product-led SaaS ready to scale. Key Highli...

Visit product View on Acquire.com SaaS

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Actual performance

$56,000/yr

Made the leaderboard

Traction signals

Asking price$1,000,000

Annual revenue$672,000

Revenue multiple1.5x

Launch Intel predictions

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

84%84% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

81%81% 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 · Strong signals: personal, month, profitable · Missing: mobile apps, ios, entrepreneurs

60%60% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

57%57% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

43%43% 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

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

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

10%10% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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