Tech Artisan Hub

Hacker News

Tech Artisan Hub

We are excited to announce the launch of our complimentary job listing platform specifically tailored for IT professionals. Our platform offers the ability to create a personalized page where you can create your resume and showcase your recent projects in a dedicated portfolio section. Leveraging advanced AI technology, we ensure that businesses can effortlessly identify and connect with suitable candidates. Here are some of the key features our platform provides: 1. Utilize our AI system to search for job openings. 2. Use our AI system for cover letters. 3. Use our AI system to build a great resume 4. Personal user page with resume and portfolio page. 5. Save job listings for future review 6. Message system We invite you to create your personal page with us. Once we have user pages we will be contacting companies to search talent and post their job openings.

Visit product View on Hacker NewsMay 30, 2024

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

88%88% 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.

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

40%40% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: user, open · Missing: mac, agents, macos

38%38% 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 · Missing: plus, intuitive, reviews

30%30% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: excited, ide, io · Missing: https docs, just released, exist

30%30% 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 · Missing: arr, mrr, revenue

11%11% 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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