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Social Bellow – AI-Powered Interactive Companion

Hacker News

Social Bellow – AI-Powered Interactive Companion

Greetings HN, My name is Edgar and I've created Social Bellow, an AI chat companion. Before this I spent close to a decade working on games with Grumpyface Studios, working closely with Cartoon Network as well as managing my own business. I've built Social Bellow out of the need to manage prompts and eliminate the repetitive task of copying and pasting the same prompts. Storing prompts has the added advantage of providing Large Language Models (LLMs) with more context, thereby facilitating structured content responses. Moreover, I saw the necessity for a tool that could maintain the context window during conversations with the LLMs. Social Bellow was built using AWS Amplify, NextJS, and the help of Vercel to do the streaming. Figma has also helped tremendously in the creation of the project. Having a workflow of Figma, Amplify Studio, and Git continuous deployment has cut down on the time to publish a change. Social Bellow is free to use with OpenAI GPT-3.5 Turbo with a token allowance of 50,000 tokens a month. I've just launched this so you'd be one of the first to try it out. Thank you for the feedback and helping improve the application!

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Actual performance

2points
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: created, ios · Missing: supports, reddit linkedin, podcasting
91%91% 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: model, models, context · Missing: mac, agents, macos
87%87% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: 000, io · Missing: https docs, excited, just released
57%57% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
47%47% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: ios, month · Missing: mobile apps, personal, entrepreneurs
42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue
10%10% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency
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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