Meetily – Open-Source AI Meeting Assistant (Alt to Otter.ai)

Hacker News

Hey HN, We built Meetily – an open-source, privacy-first AI meeting assistant for transcription, summarization, and note-taking. Unlike Otter.ai or Granola.ai, Meetily runs entirely on local hardware or self-hosted cloud infra, ensuring full data control (no cloud storage or SaaS lock-in). Why We Built This: Most AI meeting assistants store meeting data in the cloud, raising privacy and compliance concerns. Additionally, they come with expensive SaaS pricing ($8–$20 per user/month). We wanted a free, local-first alternative that: Transcribes in real-time (Whisper.cpp) Generates AI-powered summaries (Local LLMs with Ollama (Accurate with models greater than 32B parameter models), or external APIs like Claude Sonet, Groq, Llama 70B) Stores meeting data locally (no cloud dependencies) Runs on local hardware (for security & compliance) Is fully open-source (customizable & extensible) Tech Stack Frontend: Tauri + Next.js Backend: FastAPI Transcription: Whisper.cpp Summarization AI: Local LLMs (Ollama) + API support (Claude, Groq, etc.) Database: SQLite + VectorDB for semantic search Rust-based audio capture for efficiency What's next for us? Optimizing AI summarization for small LLMs Hybrid cloud support (self-hosted models for extra compute) Conversational search on past meetings

Visit product View on Hacker NewsFeb 22, 2025

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Did not reach leaderboard

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Product HuntOn track for Day 1 leaderboard · Strong signals: claude, model, user · Missing: mac, agents, macos

96%96% 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 · Strong signals: para · Missing: supports, reddit linkedin, podcasting

85%85% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: llama, io · Missing: https docs, excited, just released

79%79% 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: month, para · Missing: mobile apps, ios, personal

33%33% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: saas · Missing: arr, mrr, revenue

24%24% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: host · Missing: plus, platform, intuitive

24%24% predicted probability of success on AppSumo, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: audio · Missing: web3, chat, crypto

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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