Create a talent/services marketplace without code

Hacker News

Hi HN We are building a platform that allows anyone to create a custom talent marketplace inside your network. Think of it as Shopify but for talent : ) You can create your own board (store) in minutes, customise and invite your talent. Everything else works our of the box: profiles, matching requests and talent, support, payments, collaboration. The best part is that you make 3-10% every time someone is hired inside your board. You can use it with a link or embed inside your product/community/website. We already have YC startups like Memberstack - https://heep.so/b/memberstack among early users. The short backstory: we have originally started Heep as a marketplace for webflow/bubble developers and quickly realised that there are ton of new, niche, emerging professions. So instead of building another talent marketplace we decided to pivot and build a platform to for others to build on top. Our vision is to support any (even the most crazy) emerging talent/services use-cases: if there is a supply and demand for it we wan to help support it. It's currently in early beta and we are looking for feedback and community leaders interested in trying Heep (I will personally onboard you to the product and help you launch your board). Also here for any AMA

Visit product View on Hacker NewsMay 24, 2023

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Indie HackersFits the IH revenue-focused audience · Strong signals: started · 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: user, new, code · Missing: mac, agents, macos

67%67% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

44%44% 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: personal, users · Missing: mobile apps, ios, entrepreneurs

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

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

20%20% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

14%14% 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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