Project Overview
The project began with a customer inquiry from a live web-based automobile market: replace natural language search with a natural language aide. The goal was to allow users to simply type in queries like “Find me a safe, low-budget family car” and let the AI translate them into concrete database filters.
While initially deployed to the auto market, the architecture developed was platform-independent, equally suited to real estate listings, corporate registration sites, e-commerce product catalogs, or any environment with complicated multi-parameter search.
The Challenge
Integrating a generative AI search assistant into a live marketplace without compromising sensitive data. The AI needed to:
- Learn the database schema
- Generate valid sets of filters from free-form input
- Execute without accessing the live dataset
Additional requirements were:
- Security-first architecture with schema-only AI access
- Universal compatbility with minimal modifications to host platform code
- Stable prompts for predictable, production-quality AI results
Our Solution
We built a standalone AI search module on Next.js for both frontend and backend.
- Backend: Handles user queries using a GPT-based pipeline of prompts, returns validated filter parameters
- Frontend: Brandable, embeddable search bar that can be made appear native to any UI
AI & Security Highlights
- Schema-Only AI Access: AI does not access sensitive product or user data at all
- Prompt Engineering for Filter Mapping: Handles vague or multi-condition queries with extremely high accuracy
- Plug-and-Play Integration: Supports any structured dataset, from properties to cars to business listings
Technology Stack
- Frontend & Backend: Next.js
- AI (Generative): GPT-based model for query-to-filter mapping
- Security: Schema-level AI integration with validation layer
- UI Design: Figma prototypes for completely brandable search bar
Results
- Implemented production-level AI search in a 2-month cycle
- Achieved zero direct sensitive data access
- Provided end-to-end documentation and video integration guidelines
- Verified portability of the module to non-automotive platforms
Lessons Learned
Security-first design enables the adoption of safe AI in live environments. Restricted AI to schema-only access offers a strong balance between innovation and risk management.
Conclusion
Originally designed for the automotive market, this AI Car Search product demonstrates the capabilities of generative AI to power universal, natural language search across any platform with enhanced filtering to provide a safer, faster and more intuitive way for consumers to find exactly what they want.