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Profitable AI Lead Qualification SaaS - WhatsApp & Instagram Automation

Acquire.com

This is an AI-powered sales automation platform that qualifies leads and books appointments via WhatsApp and Instagram DMs, replacing human setters. Key metrics: $22k MRR, 80%+ net margins, 76 active subscribers, 5% churn.

This is an AI-powered sales automation platform that qualifies leads and books appointments via WhatsApp and Instagram DMs, replacing human setters. Key metrics: $22k MRR, 80%+ net margins, 76 active subscribers, 5% churn. How it works: Customers create AI assistants that engage prospects 24/7, qualify them through conversation scripts, and automatically book calls via Calendly. Target market: Online coaches, consultants, course creators, and agencies. Tech stack: Nuxt 3, Supabase, WhatsA...

Visit productView on Acquire.comSaaS
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Actual performance

$22,000/yr
Made the leaderboard

Traction signals

Asking price$499,000
Annual revenue$264,000
Revenue multiple1.9x

Launch Intel predictions

Analyze your own launch →
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
77%77% 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, profit, saas · Missing: arr, revenue, ttm
76%76% 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: profitable · Missing: mobile apps, ios, personal
55%55% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos
50%50% 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, calls · Missing: plus, intuitive, reviews
35%35% 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
28%28% 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
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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