Inspiration
Meetings generate a huge amount of information, but important decisions, action items, and discussions are often lost once the meeting ends. We wanted to build an AI-powered meeting assistant that could turn raw meeting conversations into useful, structured information and reduce the effort required to review meetings manually.
What it does
Cognition-MeetingRK processes meeting transcripts and automatically extracts meaningful information such as summaries, key decisions, action items, important discussion points, and answers to questions about the meeting. It uses a multi-agent AI approach where specialized agents work on different parts of the meeting analysis.
How we built it
We built the system using Python and a multi-agent architecture. Different AI agents are responsible for specific tasks such as understanding the meeting, generating summaries, identifying decisions and action items, and answering questions. The agents work together as a pipeline to transform an unstructured meeting transcript into structured and actionable output.
Challenges we ran into
One of the biggest challenges was making multiple AI agents work together reliably while maintaining consistency between their outputs. We also had to handle long and unstructured meeting transcripts, design effective prompts for each agent, and ensure that the final information was accurate and useful rather than simply generating a generic summary.
Accomplishments that we're proud of
We successfully created a working multi-agent meeting assistant that can break down complex meeting conversations into several useful outputs. We are especially proud of using specialized AI agents instead of relying on a single prompt, making the system modular and easier to extend with additional meeting-analysis capabilities.
What we learned
This project helped us understand how multi-agent AI systems can divide a complex problem into smaller tasks and coordinate the results. We also learned more about prompt design, agent orchestration, transcript processing, and building AI systems that produce structured outputs from unstructured information.
What's next for Cognition-MeetingRK
We plan to make Cognition-MeetingRK more intelligent and practical by adding real-time meeting processing, improved question answering, speaker identification, better action-item tracking, and integrations with popular meeting and productivity platforms. Our goal is to turn it into a complete AI-powered workspace for managing everything that happens before, during, and after a meeting.
Built With
- crewai
- fastapi
- generativeai
- google-gemini
- multi-agent-ai
- postgresql
- python
- restapi
