---
title: "GenV: An Agentic Workflow for Actionable Insights from Google Meet Recordings"
url: https://daily.dev/posts/genv-an-agentic-workflow-for-actionable-insights-from-google-meet-recordings-dvhbukp5f
source_url: https://mlops.community/genv-an-agentic-workflow-for-actionable-insights-from-google-meet-recordings/
type: article
source: "MLOps Community"
published: 2025-05-12T14:52:23.441Z
updated: 2025-05-12T14:52:40.509Z
tags: ["genai", "gcp", "mlops"]
reading_time: 7
upvotes: 0
comments: 0
language: en
---

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# GenV: An Agentic Workflow for Actionable Insights from Google Meet Recordings

**[MLOps Community](https://daily.dev/sources/mlopscommunity)** · 7 min read · 0 upvotes · 0 comments

## Summary

GenV is a Python notebook designed to extract actionable insights from Google Meet recordings using Vertex AI's Gemini models. It automates the tedious process of analyzing meeting videos to identify key takeaways, action items, and decisions made. The workflow involves setting up Google Cloud storage, analyzing data with structured output schemas, and presenting insights in a user-friendly format. This approach enhances meeting productivity and knowledge sharing by efficiently summarizing video content.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://mlops.community/genv-an-agentic-workflow-for-actionable-insights-from-google-meet-recordings/>

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---

Tags: [#genai](https://daily.dev/tags/genai), [#gcp](https://daily.dev/tags/gcp), [#mlops](https://daily.dev/tags/mlops)

[View this post on daily.dev](https://daily.dev/posts/genv-an-agentic-workflow-for-actionable-insights-from-google-meet-recordings-dvhbukp5f)