Inventory Search Engine for Auto Parts Retailer

Azati designed and developed an AI-powered inventory search engine for auto parts retailers, enhancing traditional parts search algorithms. The solution helps customers find auto parts, automotive parts, and accessories quickly and accurately. It analyzes user input, looks for a specific entry in the auto parts inventory, and if the algorithm can’t find the requested item, it explores product characteristics and returns a list of similar automotive parts and accessories.

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All Technologies Used

Python
Python
Flask
Flask
React
React
Tornado
Tornado
Memcached
Memcached

Motivation

A Brazilian auto parts retailer with an online catalog of over 500,000 auto parts and 100,000 automotive accessories faced slow and inaccurate search results. Traditional search solutions could not handle the massive auto parts database, resulting in poor customer experience. Azati’s goal was to create an AI car parts search engine that optimized the process of finding auto parts online, improving both speed and accuracy. The new auto parts lookup software replaced the ineffective legacy system with a scalable solution capable of handling large datasets in real time.

Main Challenges

Challenge 1
Handling multiple catalog formats

The client’s auto parts inventory data was spread across XLSX, TXT, CSV, MySQL databases, and APIs. Azati developed universal data connectors to unify the catalog and standardize information. This enabled fast processing and indexing for auto parts search software.

Challenge 2
Building an intelligent search engine

The parts search engine had to quickly analyze user queries, match them against product attributes, and return highly relevant results. Azati introduced AI-powered auto parts tagging with unique attributes, enabling accurate car part finder functionality.

Challenge 3
Real-time data lookup and UI updates

The retailer required instant auto parts lookup while users typed queries. Azati implemented an in-memory search solution that bypassed database bottlenecks, ensuring real-time search updates for a seamless customer experience.

Key Features

  • Universal Data Connectors: Handles multiple catalog formats (XLSX, TXT, CSV, MySQL) and converts them into a standardized format for processing.
  • Smart Tagging for Auto Parts: Every part is enriched with unique attributes, making AI car part finder searches highly precise.
  • Real-time Search Updates: Provides an instant, dynamic user experience with real-time updates to search results as the user types.
  • In-memory Search Engine: Auto parts search results are quickly retrieved from memory to avoid disk bottlenecks, making data lookups extremely fast.
  • Modular System Architecture: The solution is divided into two key modules: one for data processing and another for user interface generation, allowing for easy scaling and maintenance.

Our Approach

Identifying Key Challenges and Defining the Solution
Azati recognized the retailer’s need to unify fragmented catalogs and improve auto parts search engine accuracy. The solution was a modular system, balancing search-engine databases for automotive data with a dynamic React UI.
Developing the Data Processing Module
Custom parsers and ETL pipelines were created for different sources (databases, spreadsheets, APIs). For huge automotive databases, asynchronous queries were implemented speeding up auto parts lookups across multiple systems.
Leveraging React for Dynamic UI
React enabled a fast auto parts search interface with live filtering, find parts autocomplete, and zero page reloads. This improved customer engagement in the auto parts eCommerce platform.
Optimizing Search with Enhanced Algorithms
Azati applied a pairwise comparison algorithm at the core of the engine, powering AI-powered parts search. This ensured fast, precise car parts search results and improved handling of complex user queries like “find engine for Honda Civic 2017”.

Project Impact

Azati’s intelligent AI search engine for auto parts retailers transformed the customer experience. The solution reduced parts lookup time to under one second and improved accuracy of auto parts search results. By implementing auto parts inventory software with AI, the retailer can now handle massive data volumes efficiently, providing users with a fast, accurate, and scalable way to find parts, accessories, and engines. This innovation positions the client as a modern automotive eCommerce leader, capable of competing with marketplaces like Autotrader parts and A&A Auto Parts.

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