VehiQL

VehiQL-

Inspiration

The idea for VehiQL sparked from our love for cars and the hassle of finding reliable, detailed automotive information online. We wondered: what if you could identify a car with a photo and explore its story instantly? This vision drove us to create an AI-powered platform to revolutionize car discovery.

What it does

VehiQL lets users search for cars by uploading images, explore detailed insights on models, compare specs, and read blogs on the latest automotive trends. It’s a one-stop hub for car enthusiasts and curious minds alike.

How we built it

We crafted VehiQL using a mix of technologies: a convolutional neural network (CNN) for image recognition, a Node.js and MongoDB backend for data management, and a React frontend for a sleek interface. A CMS powers the blog feature, keeping content fresh and dynamic.

Challenges we ran into

Training the AI to recognize cars from varied images—dealing with poor lighting or odd angles—was tough. We also struggled to organize vast car data efficiently without slowing down the platform, requiring optimized queries and caching solutions.

Accomplishments that we're proud of

We’re thrilled to have built a functional image-search feature that accurately identifies cars. The positive feedback from early users on the intuitive design and detailed insights has been a major win for us.

What we learned

We gained deep insights into AI model tuning and database optimization. User feedback taught us the value of prioritizing features like comparisons, shaping VehiQL into a more user-centric tool.

What's next for VehiQL

Next, we plan to enhance AI accuracy, add more car models, and introduce community features like user reviews. Our goal is to make VehiQL the ultimate automotive exploration platform!