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Fileport – Teleport Your Files

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Fileport – Teleport Your Files

Hello HN, Fileport is an online service that provides the fastest way to send files over the internet. Typically, email providers have file size restrictions and online cloud storage can be cumbersome to use. Fileport is the simplest way of transferring large files from point A to B. Intended for creative individuals like artists, video/audio editors, photographers showcasing their work or anyone whose work depends on exchanging large files. Fileport is capable of “streaming” files to the recipient (or multiple recipients) as you upload them. You can upload multiple files or folders which can be downloaded in a compressed format, even while uploading. Files are automatically checksummed for integrity during the upload process. There is a subscription available for users that require more features, like Photobooks. Photobooks are online photo & video albums that provide an ultra fast and clean web interface with all original files available for download. Files up to 2 GB can be uploaded by anyone without the need of an account.

Visit productView on Hacker NewsJan 23, 2023
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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.
Product HuntOn track for Day 1 leaderboard · Strong signals: user, email · Missing: mac, agents, macos
66%66% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Strong signals: interface, users · Missing: plus, platform, intuitive
55%55% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: video, users, way · Missing: mobile apps, ios, personal
48%48% predicted probability of success on TrustMRR, 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
48%48% 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 · Strong signals: subscription · Missing: arr, mrr, revenue
17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: audio · 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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