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باز کردنAbstract Retail purchases can supplement clinical surveillance because changes in demand for some over the counter (OTC) products may appear before confirmed case reports. This article describes an early stage concept for analysing aggregated GrabMart transaction data to identify unusual changes in product demand.…
Introduction Existing systems estimate user price sensitivity primarily from spending behavior or demographic proxies. They do not systematically account for residential property values, which can indicate a user’s financial circumstances. This omission creates three limitations: Limited property insights : Existing…
The short story Consider a Friday evening. A food order arrives from a mall in the city center. One driver is nearby; another is finishing a drop off and will be available shortly; a second order from the same mall may or may not appear in the next two minutes. Dispatch the nearby driver now, or hold briefly for a…
Introduction Merchant reviews contain useful details about food quality, portion size, packaging, and value. Finding these details often requires reading many comments. Aggregate ratings simplify comparisons, but they do not explain what shaped each score. We built the Automated Merchant Review Summary System to turn…
Introduction In the first two parts of this series , we described how Grab approaches data mesh through the Signals Marketplace: a way for teams to publish, discover, and reuse trusted data products across domains. Part II introduced the foundational tools behind certification: Hubble for metadata and ownership,…
Introduction The first Jarvis Pro prototype could produce answers that sounded right. That was the problem. One early answer looked polished: it named the merchant, summarized the week, and recommended pushing promotions before the next review. It was also wrong. The merchant’s order volume was down, but the sharper…
Introduction What worried us wasn’t the hallucination, it was the subtle plausibility. Answers an engineer could easily read past and accept: a right looking Structured Query Language (SQL) query, a plausible tool call, an innocent profile update, or a patch that satisfied the surface tests. When we analyzed the row…
Introduction At Grab, analytics sits close to almost every decision that matters. Our north star is the democratisation of intelligence, ensuring that anyone making a business call has immediate access to trustworthy answers. Over the last two years, model capability has crossed a threshold enabling this shift.…
Introduction The efficacy of semantic search relies on the accuracy of the underlying Knowledge Graph (KG). In high velocity domains like on demand food delivery or e commerce, the catalog of entities like dishes, products, and merchants changes rapidly. Current methods for KG construction and maintenance face three…
Part 1: From one support bot to a framework At Grab, AI agents have evolved from interesting team prototypes into production services used every day by millions of merchants, drivers, and consumers. Today, more than 500 services run on our internal agent framework, over 50 Model Context Protocol (MCP) servers are…
