ML-Powered Search Optimization for Enhanced Customer Experience

Client: Fact Finder. Industry: eCommerce — Medium & Large Companies. FactFinder, a leader in eCommerce solutions, sought to develop AI-powered tools to improve search result accuracy and relevancy for its end-users. The goal was to leverage language models to optimize search content parsing and extraction from multiple formats, including JSON, HTML, PDF, image, and video. This project aimed to enhance user experience across major retailers such as Spar, DOUGLAS, OBI, Sthil, InterSport, and Boots.

The project

Why the Client Needed co.brick Services:

FactFinder required a skilled development and consultation team to create a custom tool capable of accurately categorizing and displaying search results based on content metadata. They needed expert advice on API integrations for both FactFinder NG and OpenAI while ensuring a smooth and reliable development process. The client turned to co.brick for its proven expertise in DevOps, machine learning, and large-scale software integration projects.

Challenges

Parsing was crucial, but handling the wide variety of content formats presented a significant challenge.

Results

The tools were designed for medium to large eCommerce businesses looking to improve their customers’ search experiences. FactFinder’s key clients include well-known brands like Spar, DOUGLAS, and Boots, who seek efficient, AI-driven solutions for accurate content categorization and search result optimization.