Better context, better matches: An AI love story (for dogs)

Pup Finder is an innovative Next.js application designed to enhance user experience in searching for adoptable dogs by replacing traditional database filters with a simple text input, allowing users to describe their ideal dog in plain language. Utilizing AI and Sanity's structured data, it intelligently matches user descriptions with potential dogs, providing a more intuitive and natural search process. The project demonstrates how Agent Context, a tool that integrates AI with structured data, can transform search experiences beyond dog adoption, applicable to various domains like real estate and e-commerce. By leveraging AI to interpret user intent and structured data to enforce precise constraints, Pup Finder offers a conversational and efficient interface for finding the perfect pet, showcasing how AI can bridge the gap between user inquiries and complex data sets. The application was developed swiftly using Sanity MCP server and Agent Skills, highlighting the potential for rapid prototyping and deployment in user-focused applications.

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