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Automated Merchant Review Summary System

1 post · Sep 2026

What this trail covers

Grab has developed an Automated Merchant Review Summary System to transform unstructured customer reviews into concise, topic-based summaries. This system employs representative sampling, LLM-based summarization and quality control, and a feedback-driven regeneration pipeline to ensure summaries are accurate, relevant, and up-to-date. The goal is to provide consumers with easily scannable insights and merchants with actionable feedback on food quality, portion size, packaging, and value.

All Grab trails
  1. Automated merchant review summary system with integrated feedbackThis post details the technical pipeline for the Automated Merchant Review Summary System. Key contributions include: 1. Representative sampling using stratified sampling based on merchant rating distribution and sentiment analysis to ensure sample diversity. 2. LLM-based generation of overall and topic-specific summaries (e.g., taste, packaging, portion size). 3. LLM-based quality control to validate summary claims against source reviews. 4. A feedback-driven maintenance flow with triggers for new reviews and consumer feedback to regenerate summaries. The system aims to improve consumer understanding of merchant offerings and provide merchants with actionable insights.