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/ This is an old post in HN (https://news.ycombinator.com/item?id=5360453), but could not get enough response, so posting again, A friend told me that 'Show HN' will help better. */ Hi All, (http://www.mistrics.com/) I made a project that helps in documenting Academic projects and sharing them with teachers. It also provides facility to ask questions. Students needs to simply create projects, after that just create task and documents under it. Also inviting others into team and so on.... In Indian colleges this process is all manual right now. And I am trying to get this process online. I am not getting any traction so far. Any clue what's wrong with that? Regards,

Visit product View on Hacker NewsMar 19, 2013

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

71%71% 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 · Missing: plus, platform, intuitive

53%53% predicted probability of success on AppSumo, 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

49%49% 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 · Missing: mobile apps, ios, personal

41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

30%30% predicted probability of success on Product Hunt, 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 · 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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