PulseWire

Inspiration

We wanted to create a tool that gives product managers real time visibility into how customers feel. While companies track metrics like sales or the usage, emotional feedback is often not used often across platforms. We imagined a dashboard that takes into account customer sentiment and actional insights with the power of AI

What it does

Streams live customer feedback Analyzes sentiment and detects spikes in complaints or praises

How we built it

We sectioned the program into client and server components to handle the front end and back end. We used React for the front end and fastAPI for the back end, so we can analyze feedback and sentiment analysis in real time. We implemented a user authentication page to secure data by user, utilizing Text Blob to classify responses. The result was returned as JSON and rendered on the frontend.

Challenges we ran into

Integrating APIs cleanly between frontend and backend within the time given. Managing different branches and avoiding Git conflicts Having problems with the code which slowed our push commit into github.

Accomplishments that we're proud of

Built a functional proof of concept in under the 24 hours Created a responsive dashboard UI that updates live

What we learned

How to synchronize frontend and backend development across multiple contributers Being able to use AI for true data analysis co co-pilot.

What's next for PulseWire

The next steps for PulseWire include increased metrics outputted by the machine learning algorithm. We want to gain feedback for each product by using multimodal ai and make it an efficient tool for product management by gaining insight through multiple different sources of data.