This is a submission for the AssemblyAI Voice Agents Challenge
What I Built
We’ve all been there — back-to-back Microsoft Teams meetings, and by the time one ends, you’ve forgotten the key takeaways from the last. 😅
What if your meetings could summarize themselves?
Well… I built just that. 💡
Instead of manually rewatching recordings or relying on scattered notes, I built an AI-powered automation system that transcribes, analyzes, and summarizes meeting recordings — all thanks to AssemblyAI. 🦾🎧
🚀 Why AssemblyAI Was the Core Engine
AssemblyAI made this project possible. Here’s what stood out:
✅ Fast and accurate transcription of long-form audio
✅ Support for punctuation, paragraphing, and timestamps
✅ Easy-to-use API — literally a few lines of Python and I had readable transcripts
✅ LeMUR integration (Language Model for Understanding & Reasoning)
Here’s a code snippet that kicked it all off:
Demo
<– https://youtu.be/ZqMY-5OZD34 –>
GitHub Repository
<– https://github.com/AravindFLASH/AssemblyAI/tree/main –>
Technical Implementation & AssemblyAI Integration
🎤 First Attempt: LeMUR by AssemblyAI
I initially tried AssemblyAI’s LeMUR, a brilliant summarization engine that works right after transcription.
It almost felt like magic… until reality hit:
😬 Trial limits on LeMUR meant I couldn’t process full-length recordings.
While the API was intuitive and powerful, the constraints cut the experiment short.
So, I pivoted.
🔁 Switching to Google Gemini for Summarization
To overcome this, I decided to decouple transcription and summarization:
I continued using AssemblyAI for transcription, which is fast and reliable.
Then passed the transcribed text to Google Gemini, a powerful multimodal LLM, to generate structured meeting summaries.
This combo worked well:
AssemblyAI handled speech-to-text conversion.
Gemini extracted key points, decisions, and action items with impressive detail.
📄 A Sample Output Looked Like This:
🔮 What’s Next: Future Deployment Ideas
The vision doesn’t stop here. Here’s where I’m taking it:
🤝 Integrate summaries into Azure DevOps to auto-create work items
🧪 Run Sentiment Analysis on meeting tone for feedback culture
🗣️ Use Speaker Diarization to tag “who said what”
📅 Sync with calendar to auto-label topics, agenda, and participants
🌍 Multilingual support for global teams
💬 Final Thoughts
This project is powered by the superb transcription capabilities of AssemblyAI, with a touch of LLM flexibility when needed. 💥
Whether you’re building for productivity, compliance, or just to reclaim your time — this kind of system can be your AI-powered meeting assistant.
🎯 AssemblyAI isn’t just a transcription tool — it’s the brain behind understanding your conversations. 🧠💬
My deepest gratitude to AssemblyAI. Their industry-leading Speech-to-Text API was the essential backbone of our AI-powered meeting report solution, enabling accurate transcription that fuels our Gemini AI analysis. Thank you for empowering our innovation!