Case study - Multi-agent app

Agent Meeting Room makes local AI agents easier to use as a working session.

A Flask workspace for running structured AI meetings with local Ollama agents and optional cloud advisors, built around saved context, meeting presets, and reviewable transcripts.

View source Ask about the app
PROBLEM

Raw chat tools are weak at structured planning: context gets scattered, agent roles blur, and useful conclusions are hard to export.

BUILD

The app organizes AI agents into reusable meeting presets, streams responses, saves memory, and exports Markdown transcripts.

SAFETY

Local-first operation keeps private experiments off public hosting unless a specific demo or release is intentionally prepared.

Recent workflow upgrade

Added an asset-pipeline review style inspired by Image Cockpit workflows while keeping manual handoff safety: no copied third-party code or assets, no API keys, and no autorun wiring.

Why it matters

This shows product thinking around AI tools: not just prompt calls, but roles, memory, presets, exportable outputs, and human approval gates.