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Bitbox.co – Cloud Storage for Developers

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Bitbox.co – Cloud Storage for Developers

I've decided to bite the bullet and release Bitbox.co and get some feedback. I've been coding for years and one of the things I constantly see companies do is write and rewrite a document storage system, so I decided to write one for them. Bitbox.co uses cloud storage (currently Azure) to store documents but can be coded to use any cloud service. Documents can be public or private and URLs to that document can be used directly in HTML. There are currently a list of WebAPIs for developers to use as a tool, or build an entire system around. This is an MVP and it's simple. Upload a file, get a token; like a valet or coat check. When you want that file back, send the token and you get a byte stream. There is also a built in file converter, so you can can upload a docx file and retrieve it as a pdf by appending .pdf to the URL, for example: https://www.bitbox.co/files/1.pdf , or perhaps a tiff: https://www.bitbox.co/files/1.tif . Files can be marked as public or private, and account owners can invite other users to join their team with read, write or admin privileges. There are some directions I want to possibly go: - Allow users to select their own cloud store (Azure, AWS, etc) rather than the built in store. - Allow users to replicate their files between cloud stores, so you would store your documents on all your cloud stores in Azure or AWS, etc. - Folder structures for organization - Integration with third party platforms like WordPress or SurgarCRM - Cookbook for code examples on how to connect through the WebAPI in various languages. - Local install so developers can use their internal SMB shares to store files. - File level security, and / or folder level security for users / files. This was designed for IT departments without a strong development team to save money. Does anyone have a need for something like this? www.bitbox.co

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
86%86% 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, coding, code · Missing: mac, agents, macos
69%69% 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
50%50% 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: users · Missing: mobile apps, ios, personal
44%44% 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
32%32% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
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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.

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