The client wanted to replace rigid keyword-based search with a smarter system that allows shoppers to type queries in natural everyday language. They required the solution to handle complex product searches with multiple constraints, functional feature requirements, sentiment filters, and fuzzy matches while still returning the most relevant products. In addition, the client needed a way for business teams to easily influence and control results by applying rules for promotions, compliance, or geo-targeted visibility without depending on technical dashboards or development teams.
CLIENT’S REQUIREMENT
The client wanted to replace rigid keyword-based search with a smarter system that allows shoppers to type queries in natural everyday language. They required the solution to handle complex product searches with multiple constraints, functional feature requirements, sentiment filters, and fuzzy matches while still returning the most relevant products. In addition, the client needed a way for business teams to easily influence and control results by applying rules for promotions, compliance, or geo-targeted visibility without depending on technical dashboards or development teams.
Solution
We built an AI-powered shopping companion that understands user intent across a wide range of scenarios and returns accurate, context-aware results. The platform allows shoppers to express multiple constraints in a single query, specify detailed product features and specifications, filter results based on trust signals like ratings and reviews, or search in broad categories without naming a product directly. It also supports conversational refinements, where follow-up instructions are remembered and applied in context, along with intent-based ranking that adjusts results depending on whether the shopper is looking for budget-friendly or premium options.
Even in cases where an exact product match is not available, the system provides the closest alternatives by interpreting meaning rather than just keywords. On the business side, we designed a natural language admin interface that allows retailers to boost or suppress products, enforce compliance rules, and apply conditional filters such as geo-based restrictions through simple everyday instructions. This combination of user-focused discovery and admin-driven control creates a shopping experience that is both intuitive for customers and strategically valuable for businesses.
Technology Stack
Flask (Python Backend), MySQL, Qdrant (Vector Database), React.js, Tailwind CSS, Google Gemini AI (LLM & Embedding Generation), Docker
