ProdAI

landing page
product results page
landing page
product found
landing page
landing page
landing page
product search page
signup page

Inspiration

We were inspired by the need to simplify online shopping and help users make faster, smarter decisions. With the rise of AI, we saw an opportunity to streamline product searches and provide personalized recommendations.

What it does

ProdAI is an AI-powered product research assistant that provides personalized product recommendations based on user preferences like budget, product type, and key features. It helps users find the best products quickly, offering pros, cons, and user reviews for each item.

How we built it

We used Next.js for the frontend, Firebase for authentication, and Amazon DynamoDB for data storage. The AI recommendation engine was built using machine learning to analyze user inputs. We also integrated Google OAuth for easy sign-ups and tailored the design with Framer Motion and Tailwind CSS for a smooth user experience. We have deployed the website using AWS Amplify.

Challenges we ran into

We faced challenges in building a reliable recommendation system, integrating third-party APIs, and ensuring smooth authentication with Google OAuth. Balancing performance while delivering real-time data was also a hurdle.

Accomplishments that we're proud of

We’re proud of our AI recommendation system, Google OAuth integration, and the responsive, user-friendly design. The platform's seamless functionality and polished UI are standout achievements. Smooth integration of important AWS services such as DynamoDB and Amplify.

What we learned

We learned a lot about building AI-driven recommendation engines, integrating APIs, and handling user authentication. We also improved our skills in creating responsive UIs and managing backend systems efficiently.

What's next for ProdAI

We’re continuing to build out the Categories and Deals pages for better user experience. These features will allow users to explore different product types and find exclusive deals more easily. We also plan to add AI-driven features like image recognition and voice-based assistance, expand the product database, and improve the recommendation algorithm based on user feedback.