FilesWorkflow – File Processing Workflows Online

Hacker News

I'm excited to introduce you to FilesWorkflow, a platform designed to help you create and automate file processing workflows directly in your browser. With FilesWorkflow, you can either write your own code or use existing tasks to combine them into custom workflows. The platform features a simple and intuitive interface that makes it easy for users of all technical levels to build and execute their workflows. Currently, FilesWorkflow is in its early stages, and while we have a solid foundation, the available tasks are still limited. We invite everyone to try it out and encourage you to create more tasks to unlock even greater possibilities! We encourage you to explore the platform, create your own workflows, and share your feedback with the us.

Visit product View on Hacker NewsAug 19, 2024

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2points

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

78%78% 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, tasks, code · Missing: mac, agents, macos

75%75% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: excited, exist, existing · Missing: https docs, just released, lua

71%71% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

61%61% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

22%22% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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 · Strong signals: introduce · Missing: web3, chat, crypto

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

Incorrect prediction on native model

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