-
Engineering · Data Science · Product
Road localisation in GrabMaps
With GrabMaps powering the Grab superapp we have the opportunity to improve our services and enhance our map with hyperlocal data. No matter the use case, road localisation plays an important role in Grab’s map-making process. However, road localisation entails handling a substantial volume of data, making it a costly and time-consuming endeavour. In this article, we explore the strategies we have implemented to drive down costs and reduce processing times associated with road localisation. -
Engineering · Security
Graph modelling guidelines
Graphs are powerful data representations that detect relationships and data linkages between devices. This is very helpful in revealing fraudulent or malicious users. Graph modelling is the key to leveraging graph capabilities. Read to find out how the GrabDefence team performs graph modelling to create graphs that can help discover potentially malicious data linkages. -
Engineering · Data Science
LLM-powered data classification for data entities at scale
With the advent of the Large Language Model (LLM), new possibilities dawned for metadata generation and sensitive data identification at Grab. This prompted the inception of our project aimed to integrate LLM classification into our existing data management service. Read to find out how we transformed what used to be a tedious and painstaking process to a highly efficient system and how it has empowered the teams across the organisation. -
Engineering · Data Science
Scaling marketing for merchants with targeted and intelligent promos
Apart from ensuring advertisements reach the right audience, it is also important to make promos by merchants more targeted and intelligent to help scale their marketing. With Grab’s innovative AI tool, merchants can boost sales while cutting costs. Dive into this game-changing tool that’s reshaping the future of marketing and find out how the Data Science team at Grab used automation and made promo assignments a more seamless and intelligent process. -
Engineering · Data Science
Stepping up marketing for advertisers: Scalable lookalike audience
A key challenge in advertising is reaching the right audience who are most likely to use your product. Read this article to find out how the Data Science team improved advertising effectiveness by using lookalike audiences to identify individuals who share similar characteristics with an existing consumer base. -
Engineering · Data Science · Product
Building hyperlocal GrabMaps
Being hyperlocal is a key advantage for GrabMaps. In this article we will explain what being hyperlocal means and how it helps GrabMaps bring value to our driver-partners and passengers through the Grab platform. -
Engineering
Streamlining Grab's Segmentation Platform with faster creation and lower latency
Since 2019, Grab's Segmentation Platform has served as a comprehensive solution for user segmentation and audience creation across all business verticals. This article offers an insider look at the platform's design and the team's efforts to optimise segment storage, ultimately reducing read latency and unlocking new segmentation possibilities.

An elegant platform
Supporting real-time data streaming enables our internal users to build intelligent applications and services, a crucial aspect of continuously out-serving our community. Read this article to understand our journey of building a real-time data streaming platform from pure Infrastructure-as-Code towards a more sophisticated control plane, and the benefits of this solution.

