Understanding visual trends with AI: How we analyze web design at scale

An AI-driven system was developed in-house using open-source technologies to analyze and interpret visual design elements of websites, ensuring privacy compliance and cost efficiency by avoiding third-party vendors. The system, powered by the advanced vision-language model Qwen2-VL-7B-Instruct, integrates Vision Transformer technology and supports dynamic resolution and multilingual processing, making it suitable for large-scale applications. Text generation is enhanced through the vLLM library, which optimizes memory usage and parallel processing across GPUs. Deployed on AWS with SkyPilot, the system handles workloads efficiently by dynamically distributing tasks across an 8-GPU NVIDIA L40 cluster. The analysis process involves multiple asynchronous insight agents managed via a Dockerized FastAPI application, each responsible for specific aspects of a website’s design. Insights are aggregated and returned in a structured JSON format, providing a comprehensive overview of a site's design and performance metrics.