Pitch It Perfect

Sample Project Creation Page

Inspiration

History isn’t just shaped by great ideas, but by those who can share them powerfully. We’re here to help innovators turn complexity into clarity, ensuring their ideas don’t just exist—but inspire. As Maya Angelou once said, "I've learned that people will forget what you said, people will forget what you did, but people will never forget how you made them feel," and we want to make them FEEL the presentation!

What it does

Pitch provides you with tailored feedback and detailed statistics on your pitching performance. Leveraging the power of NLP, computer vision, and our seamless interplay of data collection and analysis, we bring users comprehensive feedback from the overall tone, strength, and lacking area of the delivery to the visualization of their volume and pitch control.

How we built it

We leverage Next.js's dynamic rendering capabilities alongside Flask's robust support for Python libraries, particularly those essential for sentiment analysis and Google Cloud integrations. Features that we chose to analyze include filler words, text sentiment, voice modulation, word pacing, emphasis, persuasiveness, and GenAI-tailored constructive feedback.

Challenges we ran into

Maintaining balance between the complex backend integration (distinct frameworks and analysis models) and designing our frontend for a pleasing user experience was a challenge we were very excited to tackle.

Accomplishments that we're proud of

Since this is one of our first fully developed full-stack web applications, we're proud of the ambitious leap we've taken and the time and dedication our team puts into getting this project running smoothly. Our gaze accuracy detection visualization is also super cool, but due to the time constraint, we've yet to implement the feature in our current version.

What we learned

Some people assume that big success follows from making enough small success, but we realize from building this project, it's rather from making enough failures that we reach big success.

What's next for Pitch It Perfect

With the data collected through use, we believe we can train another AI model that can perform multilayer analysis of the vast data pool we were able to collect, understanding how each variable interplays and creating the pitching result that we see. Through it, we could make the model better understand an individual's style and give better quality feedback in the process. What naturally follows is also more language integration, reaching and helping more users realize their dream through communication.