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I made a All-in-One app for Freelancers
Hacker NewsI made a All-in-One app for Freelancers
I made a web app for Freelancers or anyone else who needs a platform to manage projects, communicate with clients, send invoices, and organize files seamlessly. I'm a freelancer, and I was always frustrated with juggling Google Drive, email, Trello, and chat—all over the place. So, I decided to build this solution. https://collabodev.lucination3d.com
Share cardActual performance
3points
Did not reach leaderboard
Launch Intel predictions
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TrustMRRFits verified-revenue profile · Strong signals: google, way · Missing: mobile apps, ios, personal61%61% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released46%46% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting43%43% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews39%39% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: google, email · Missing: mac, agents, macos29%29% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency12%12% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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