Problem

Transcribify, a video transcription platform, faced issues with accuracy and user engagement. The existing platform lacked intuitive features and had slow API response times, leading to poor user experience. Additionally, the platform struggled with scalability during peak usage times.

To address these challenges, the team needed to improve transcription accuracy, enhance user engagement, reduce API response time, and ensure seamless scalability.

Learn more about Transcribify here.

Solution

The team at Transcribify developed a solution that integrated Amazon Transcribe and various AWS services like Comprehend. This integration resulted in a 30% improvement in transcription accuracy after conducting comprehensive user research. They also designed an intuitive frontend using React.js and Next.js that provided real-time updates on user meetings.

The backend was built using Django which reduced API response time by 40%, ensuring swift video uploads, efficient job management, and prompt transcription retrieval. To enhance user engagement and interaction, they introduced features such as annotations, note-taking, and summarizing resulting in a 25% increase in engagement. The team also overcame scalability challenges to facilitate seamless user experience even during peak usage times.

Impact

Achieved 30% improvement in transcription accuracy
Reduced API response time by 40%
Fostered a 25% increase in user engagement and interaction

Quote of how incredible of an impact this had.

Team

Team Member #1 - Software Engineer
- Oversaw the integration of Amazon Transcribe and various AWS services, resulting in a 30% improvement in transcription accuracy
- Built the intuitive frontend using React.js and Next.js, providing real-time updates on user meetings
Team Member #2 - Backend Developer
- Built the backend using Django, reducing API response time by 40%
- Overcame scalability challenges to facilitate seamless user experience even during peak usage times

Transcribify Improves Accuracy, Speed, and Engagement