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Jinee AI
Meetings of the Future
104 followers
Meetings of the Future
104 followers
Every meeting, someone asks a question nobody can answer. The data exists — in Slack, Databricks, your dashboards — just never where you need it. In the meeting. Jinee AI joins your call and speaks. Ask it a question, it pulls real data from your systems and answers out loud. Not after the meeting. Not in a follow-up. Right there. Not a note-taker. A participant.
Hey Product Hunt! 👋
I'm Chirag, co-maker of Jinee - an AI agent that joins your Google Meet calls and actually participates.
😩 The problem: We've all been in meetings where someone asks "what did we decide last week?" or "what's the latest ?" and the next 10 minutes are spent digging through docs, Slack threads, and memory. Meanwhile, meeting notes either don't get taken, or they're so sanitized they're useless.
🤷 Why existing tools fall short: Most meeting AI tools sit outside the call, they record, transcribe, and hand you a summary after it's over. That's useful, but it doesn't help you in the moment when you actually need answers.
✨ What Jinee does differently: Jinee joins your meeting as a participant. Say "Jinee" and ask a question; it listens, understands context, and responds out loud in real-time. Think of it as a teammate who's always prepared, never forgets, and never talks unless spoken to. 🤐
⏰ Why we built this now: Real-time speech AI finally got fast enough and good enough to make this feel natural, not gimmicky. The gap between "cool demo" and "actually useful in a real meeting" just closed.
🔑 Key benefits:
🎙️ Answers questions live - no more "let me get back to you on that"
🙌 Hands-free, voice-activated - no tab-switching or typing mid-conversation
💻 Works inside Google Meet - no new app for your team to adopt
📝 Meeting summaries delivered after the call so nothing falls through the cracks
We'd love for you to try it and tell us what breaks 🛠️ Seriously — we're early and every piece of feedback shapes what we build next.
Yomio
I really like how Jinee highlights key information in real-time during meetings. Throughout my career, I’ve heard “I don’t remember that” or “we need to refine the documentation” far too many times.
That said, when thinking about enterprise adoption, data privacy becomes critical. How is sensitive meeting data handled? What guarantees are there around storage, retention, and model training?
Integrating LLMs into work pipelines is powerful, but the risk of data leakage is a real concern for companies. I’d be very interested to learn more about how Jinee approaches security and privacy at scale.
Tried it just now, the idea seems really cool. Can't wait to see how you integrate it with datawarehouses