I developed a system that automates meeting summaries using Next.js for the frontend and Python with FastAPI for the backend. The solution utilized OpenAI APIs to convert meeting audio to text, then generate detailed summaries with metrics, questions, and key points, enhancing the efficiency of documentation and collaboration.

Frontend with Next.js: Built a dynamic and responsive user interface, allowing users to upload meeting audio files and view generated summaries easily.

Backend with FastAPI & Python: Developed an efficient backend to process audio files, transcribe them into text, and pass the data through OpenAI APIs to generate summaries, insights, and key metrics.

Integration with OpenAI APIs: Leveraged OpenAI’s models to extract valuable information from transcriptions, providing users with structured summaries and actionable insights.

Metrics & Question Generation: Created algorithms to analyze the transcriptions, extract metrics, and formulate questions based on meeting content, ensuring comprehensive summaries.

Real-Time Processing: Enabled real-time processing for audio-to-text conversion and summary generation, improving speed and usability for end-users.

This project automated the documentation of meetings, significantly reducing manual effort, improving the accuracy of summaries, and providing valuable insights that enhanced team collaboration and decision-making.