Grab's Engineering team solves critical transportation challenges and makes transport freedom a reality for 620 million people in Southeast Asia.
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-level failures, a clear pattern emerged: SQL generation: kept the query shape but…
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. Agents now do in minutes what used to take a week: preparing the data, writing queries,…
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 critical challenges: Inaccuracy and hallucination from Large Language Models…
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 registered on our remote MCP framework, and a single Large Language Model (LLM)…
Introduction: The evolution of Grab’s Data Lake At Grab’s scale, managing petabytes of data across billions of S3 objects demands more than a storage layer. It demands a robust architectural primitive that supports the high-concurrency needs of a modern “Lakehouse.” Our goal is full storage-compute separation, leveraging S3 as an elastic foundation for both near-real-time metrics and large-scale…
Introduction Counter Service is used across Grab’s anti-fraud platform to answer time-windowed count questions, such as recent ride requests by a user or failed payment attempts on a card. The service handles tens of thousands of queries per second (QPS) with about a billion requests per day, while maintaining strict requirements around latency and reliability to support real-time fraud rule…
Distroless adoption at Grab Grab is migrating from heavy base images to Distroless images to reduce security risks. By limiting each container to the application and its runtime dependencies, we shed non-essential binaries and associated Common Vulnerabilities and Exposures (CVEs). This migration is more than a compliance mandate; it is a strategic security decision to build a more resilient…
Introduction In Part 1 , we introduced Palana , Grab’s Kubernetes-native secure execution platform for autonomous AI agents. We discussed the underlying need for isolated environments and covered its core design principles: treating isolation as the unit of trust, keeping credentials out of agent hands, and mediating all network access. In this second part, we’ll dive under the hood into Palana’s…
Abstract Artificial intelligence (AI) agents are moving from experiments into everyday engineering workflows. They can read code, call application programming interfaces (APIs), run tests, create merge requests, answer Slack messages, and keep long-running state. That makes them useful, but it also changes the risk model - especially as agents get more autonomous in their use of tools. An agent…
Introduction: The journey of documentation at Grab In early 2021, Grab adopted a Docs-as-Code approach to address gaps in our technical documentation processes, as illustrated in our blog post Embracing a Docs-as-Code . Inspired by the practices of other market leaders, we integrated documentation into our engineers’ workflows, making it part of the codebase. This approach addressed our initial…