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Show HN - Conversation assistant

Hacker News

Show HN - Conversation assistant

http://sac01.herokuapp.com/ http://github.com/thebossedgar/sac2 What is it? It's a web service that you can build conversations with context for others to respond when they are available. Why? I have seen the need of communicate with people that are busy/disconnected. The use of e-mail isn't good enough when you want to have a conversation in context. I mean, you would say something depending of a previous answer. Note: Sorry for the people that may not understand the site content that is in spanish language. Will support english language soon. Workflow ============================== User create a conversation with an initial message. Then the user introduce possible answers. Then click on the Guardar declaracion button. The user gonna create a following message depending on an possible answer of the previous message. Let's say I would say "something" to you if you responde me "yes". It's just like that. When the user finish building the conversation he/she can send the link to other user to answer. When the other user answer the conversation in context the original user can see the answers. Well I hope you can understand the idea by trying the application. Thanks if you are reading at this point. If you have any question, suggestion, complain, anything, just let me know

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Actual performance

1points
Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: user, context, plain · Missing: mac, agents, macos
83%83% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
75%75% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
55%55% 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: answers · Missing: mobile apps, ios, personal
45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: soon · Missing: plus, platform, intuitive
41%41% 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
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: introduce · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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