Vetted AI-native engineering talent marketplace with 40 curated profiles

Acquire.com

A strategic talent marketplace asset focused on AI-native engineers who can configure and orchestrate modern AI coding tools. Built over 30 months, the platform sourced talent for seven enterprise clients across the US, UK, Europe, and the Middle East, generating $38K in verified revenue with no paid marketing. The sale includes a curated engineer pool, documented vetting methodology, domain, and codebase, providing a buyer with an established supply-side foundation for AI-focused recruitment...

Visit product View on Acquire.com SaaS

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Actual performance

Did not reach leaderboard

Traction signals

Asking price$99,999

Launch Intel predictions

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

87%87% 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.

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.

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

45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: coding, code · Missing: mac, agents, macos

43%43% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: revenue · Missing: arr, mrr, profit

31%31% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

29%29% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

23%23% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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