I made an AI powered SEO tool so that you never launch to 0 users again

Hacker News

Hey HN! My name is Mohammad, and I'm the founder of SEOLabs. I built this after failing 3 startups with the same problem: zero distribution plan. You can see the story here: https://www.youtube.com/watch?v=cIgGocOEm_I Most SEO tools cost $300+/month and are built for agencies, not bootstrapped founders. They're complex and assume you have a marketing team. SEOLabs uses AI to automate keyword research and content planning at founder-friendly pricing. Find low-competition keywords, get content plans, and actually rank on Google. How it works: Enter your product/niche AI finds keywords people search for Get automated content plans Ship content that ranks Takes minutes instead of hours of manual research. We're launching in 10 days. Currently accepting waitlist signups. Would love to hear what the HN crowd thinks!

Visit product View on Hacker NewsJul 31, 2025

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2points

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Did not reach leaderboard

Launch Intel predictions

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

91%91% 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.

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

74%74% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: month, google, users · Missing: mobile apps, ios, personal

47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

42%42% 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

33%33% 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 · Strong signals: bootstrapped · Missing: arr, mrr, revenue

24%24% 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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