Selldone SLDN – A Token for Decentralized Commerce

Hacker News

Hi HN, I’m Mehrdad, one of the creators of Selldone, a business operating system designed to make commerce easier, faster, and smarter. Recently, we launched SLDN, our official token on the Solana blockchain. With SLDN, we're exploring how decentralized technologies can empower businesses, marketplaces, and communities by integrating blockchain features like faster transactions and tokenized economies into our platform. What you can try: -Visit Selldone SLDN to learn about the token and how we plan to use it. -Experiment with the live integration of SLDN on our platform without needing plugins or coding. -Get insights into our vision for decentralized commerce and how SLDN might reshape how businesses operate. We’re still in the early stages and would love your feedback. Whether you’re into blockchain, ecommerce, or startups, I’d be thrilled to hear your thoughts and answer any questions about the project. Thanks for checking it out! https://selldone.com/token

Visit product View on Hacker NewsJan 22, 2025

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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.

AppSumoStrong fit for a featured deal · Strong signals: platform · Missing: plus, intuitive, reviews

56%56% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

48%48% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

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

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

37%37% 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

12%12% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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