Extensive research and development were required to ensure seamless functionality. The system needed to extract and stream 10-second video fragments from AWS storage while maintaining an uninterrupted experience. A significant security challenge was the implementation of temporary credentials (STF) that required periodic renewal every 15 minutes without disrupting the stream. Additionally, we had to ensure that each video segment was properly referenced and accessible.

Finally, dynamic signature handling was necessary to securely manage access to each video fragment without exposing sensitive information.

To address these challenges, we built the MVP from scratch using Next.js for the frontend and Python for the backend. We implemented HLS streaming with dynamically generated playlists that referenced video segments stored in AWS.

A robust security layer was developed using temporary credentials (STF), which dynamically refreshed to avoid service disruption. Additionally, we designed a dynamic signing mechanism to ensure secure and seamless access to each video fragment.

Multiple layers of security were integrated, including frequent credential revocation, to minimize risks of unauthorized access and maintain data integrity.

The result was a fully functional and secure video analysis platform, ready to implement AI features to enable data analysis. The system provides a unified video experience with a continuous timeline, despite the fragmented nature of stored video data. Our highly secure streaming solution ensures that business data remains confidential.

This project was a groundbreaking technical achievement, requiring deep research, iterative problem-solving, and the strategic integration of modern technologies.