A guide to improving marketplace search, data quality, and onboarding with LLMs

Refuel leverages large language models (LLMs) to address complex data challenges in marketplaces, enhancing workflows like supplier onboarding, product catalog quality, and trust & safety, thereby reducing costs and increasing gross merchandise value (GMV). The company distinguishes itself from general-purpose LLMs by offering tailored solutions that provide high accuracy, cost efficiency, and rapid deployment. Refuel's approach automates processes such as supplier verification, fraud detection, high-fidelity product tagging, and content review, which are traditionally human-intensive and costly. Case studies demonstrate significant operational improvements, such as reducing onboarding times, enhancing data quality, and increasing transaction volumes for large marketplaces. These successes reflect Refuel's ability to provide bespoke LLM solutions that adapt to specific marketplace needs, offering substantial time and financial benefits.