This content originally appeared on DEV Community and was authored by Aravind d
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!
This content originally appeared on DEV Community and was authored by Aravind d
Aravind d | Sciencx (2025-07-28T04:19:58+00:00) 🎙️ Turning Microsoft Teams Meetings into Actionable AI Reports with AssemblyAI 🧠💼. Retrieved from https://www.scien.cx/2025/07/28/%f0%9f%8e%99%ef%b8%8f-turning-microsoft-teams-meetings-into-actionable-ai-reports-with-assemblyai-%f0%9f%a7%a0%f0%9f%92%bc/
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