ProductPulse

ProductPulse is an AI-powered customer feedback platform that automatically analyzes reviews, prioritizes issues, and delivers real-time dashboards and executive insights for product teams.

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Inspiration

Every day, companies receive customer feedback through reviews, surveys, support tickets, and feature requests. As the volume grows, manually reading and prioritizing this feedback becomes increasingly difficult. Important issues can easily be overlooked, delaying product improvements and reducing customer satisfaction.

We wanted to build a platform that could automatically transform raw customer feedback into meaningful business intelligence using AI.

What it does

ProductPulse is an AI-powered customer feedback intelligence platform that analyzes customer feedback and automatically identifies:

Customer sentiment Feedback category Priority level Executive summaries Suggested actions Business impact

Users can upload individual feedback or bulk CSV files, and the platform generates an interactive dashboard with sentiment trends, AI insights, complaint categories, feature requests, and an executive report.

How we built it

The frontend was built using Next.js, React, TypeScript, and Tailwind CSS, then deployed on Vercel.

The backend uses Next.js API Routes with Prisma ORM to communicate with Amazon Aurora PostgreSQL, which stores customer feedback and AI-generated analysis.

Feedback is analyzed using OpenAI GPT-4o-mini, which generates sentiment, categories, priorities, summaries, suggested actions, and business impact before storing the processed results in Aurora for real-time analytics.

Challenges we ran into

One of the biggest challenges was designing a workflow that could efficiently process customer feedback while keeping the dashboard responsive. We also focused on creating meaningful AI-generated insights instead of simply classifying sentiment. Building an executive report that summarizes business impact in a concise and useful way required several iterations.

Accomplishments that we're proud of

What we learned

This project provided hands-on experience integrating AI into a real-world application while designing a scalable architecture around Amazon Aurora PostgreSQL. We also learned how to combine AI analysis, database design, and interactive dashboards into a complete end-to-end product that supports data-driven decision making.

What's next for ProductPulse

Future improvements include background AI processing for large imports, user authentication, organization-specific workspaces, real-time notifications, collaborative analytics, and advanced trend forecasting to support much larger datasets while maintaining performance.

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