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I built FluenAI to overcome my communication hurdles

Hacker News

I built FluenAI to overcome my communication hurdles

Over the past six months, I've been obsessively building FluenAI as a side project, a communication coaching tool that's essentially a personal communication skill multiplier. As someone who's spent years struggling to articulate ideas effectively in both professional and personal settings, I knew there had to be a better way. The Technology: To bring FluenAI to life, I integrated several AI technologies that essentially simulate a user's language processing model: - Retrieval-Augmented Generation (RAG): By modeling user transcripts as vector embeddings, FluenAI retrieves relevant context to deliver precise recommendations. - Large Language Models (LLMs): Utilizing models, FluenAI generates tailored insights based on individual speech patterns. - Speech-to-Text Transcription: Advanced speech recognition ensures accurate transcription of spoken words for thorough analysis. Beyond analysis, it generates personalized learning topics and resources to systematically level up your communication skills. My friends and I have been our own guinea pigs throughout development, and the results have been nothing short of transformative. Presentations have become crisper, meetings more impactful, and my overall communication confidence has skyrocketed. I’ve put together a short promotional video showcasing FluenAI: https://www.youtube.com/watch?v=Ig9-25QcitM And a more detailed video of how it works: https://www.youtube.com/watch?v=lMvlU-ABpSQ Whether you're an engineer, a startuo founder or someone passionate about communication optimization, I'd love your thoughts and feedback.

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Product HuntOn track for Day 1 leaderboard · Strong signals: model, user, new · Missing: mac, agents, macos
91%91% 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
87%87% 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
62%62% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive
61%61% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: personal, video, month · Missing: mobile apps, ios, entrepreneurs
48%48% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
15%15% 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.

Incorrect prediction on native model

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