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Supergile – Uber for professional software teams

Hacker News

Supergile – Uber for professional software teams

Like in Uber, a driver by operating a car gives you a ride — at Supergile, a dedicated project manager by operating a remote team, delivers software that matches your requirements and quality standards. As the project's complexity grows, a flat monthly rate is designed to make an effort predictable. Things that make it better than a software agency: - A curated network of professional software teams gives a virtually unlimited choice of technology stack and skills. - Frees up customers from RFPs and assessments. - Focus on operational efficiency - reflected in the pricing model. Does it make sense? Would love feedback/thoughts. I target mid-level technical executives at customer-centric software companies/products — would you use a service like this? Why and why not?

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Actual performance

2points
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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
89%89% 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: model · Missing: mac, agents, macos
69%69% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
53%53% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: month, monthly · Missing: mobile apps, ios, personal
44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
39%39% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
15%15% 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.

Incorrect prediction on native model

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