How We Built an Automated Meeting Intelligence System with Google Meet, Slack, and RAG

Hi, I'm Ryan Tsuji , CTO at airCloset — a fashion subscription service based in Japan. In previous posts, I wrote about building a DB Graph MCP server that lets you query 991 database tables across 15 schemas with natural language, and a suite of 17 MCP servers that opened our internal operations to AI. This time, it's not about MCP. It's about something more fundamental — turning meetings into a searchable knowledge base . This is the system I've wanted to build first when thinking about digitizing our company's information assets. We built a system that automatically shares Google Meet recordings and transcripts to Slack channels, and makes past meeting content searchable with natural language . The Problem: Context Disappears the Moment a Meeting Ends Face-to-face communication is fast and dense. A decision that takes 30 minutes over text can happen in 5 minutes in a meeting. That's the biggest advantage of meetings. But the problem is that context starts disappearing the moment the