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	<title>Grab Tech &#8211; Noise</title>
	<atom:link href="https://noise.getoto.net/author/grab-tech/feed/" rel="self" type="application/rss+xml" />
	<link>https://noise.getoto.net</link>
	<description>The collective thoughts of the interwebz</description>
	<lastBuildDate>Wed, 21 Oct 2026 00:23:00 +0000</lastBuildDate>
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		<title>App stability at scale with a layered defense</title>
		<link>https://noise.getoto.net/2026/10/21/app-stability-at-scale-with-a-layered-defense/</link>
		
		<dc:creator><![CDATA[Grab Tech]]></dc:creator>
		<pubDate>Wed, 21 Oct 2026 00:23:00 +0000</pubDate>
				<category><![CDATA[Android]]></category>
		<category><![CDATA[App Stability]]></category>
		<category><![CDATA[Engineering]]></category>
		<category><![CDATA[ios]]></category>
		<category><![CDATA[mobile]]></category>
		<category><![CDATA[reliability]]></category>
		<guid isPermaLink="false">https://engineering.grab.com/app-stability-at-scale-with-a-layered-defense</guid>

					<description><![CDATA[Introduction

Artificial intelligence (AI) coding assistants have changed how fast we can ship. They have not changed how mobile users experience a crash. That gap is the pressure every mobile stability program now operates under.

The Grab superapp, w...]]></description>
		
		
		
			</item>
		<item>
		<title>GrabMart data for faster disease outbreak detection</title>
		<link>https://noise.getoto.net/2026/10/13/grabmart-data-for-faster-disease-outbreak-detection/</link>
		
		<dc:creator><![CDATA[Grab Tech]]></dc:creator>
		<pubDate>Tue, 13 Oct 2026 00:23:00 +0000</pubDate>
				<category><![CDATA[AI]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[Engineering]]></category>
		<guid isPermaLink="false">https://engineering.grab.com/grabmart-data-for-faster-disease-outbreak-detection</guid>

					<description><![CDATA[Abstract

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...]]></description>
		
		
		
			</item>
		<item>
		<title>Smarter personalization: How property data helps us understand user price sensitivity</title>
		<link>https://noise.getoto.net/2026/10/06/smarter-personalization-how-property-data-helps-us-understand-user-price-sensitivity/</link>
		
		<dc:creator><![CDATA[Grab Tech]]></dc:creator>
		<pubDate>Tue, 06 Oct 2026 00:23:00 +0000</pubDate>
				<category><![CDATA[AI]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[Engineering]]></category>
		<guid isPermaLink="false">https://engineering.grab.com/price-sensitivity-profiling-using-llm</guid>

					<description><![CDATA[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 omissi...]]></description>
		
		
		
			</item>
		<item>
		<title>Powering AI-led research through simulation</title>
		<link>https://noise.getoto.net/2026/10/05/powering-ai-led-research-through-simulation/</link>
		
		<dc:creator><![CDATA[Grab Tech]]></dc:creator>
		<pubDate>Mon, 05 Oct 2026 00:00:00 +0000</pubDate>
				<category><![CDATA[artificial intelligence]]></category>
		<category><![CDATA[Dispatch]]></category>
		<category><![CDATA[Engineering]]></category>
		<category><![CDATA[Experiment]]></category>
		<category><![CDATA[machine learning]]></category>
		<guid isPermaLink="false">https://engineering.grab.com/powering-ai-led-research-through-simulation</guid>

					<description><![CDATA[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 tw...]]></description>
		
		
		
			</item>
		<item>
		<title>Automated merchant review summary system with integrated feedback</title>
		<link>https://noise.getoto.net/2026/09/25/automated-merchant-review-summary-system-with-integrated-feedback/</link>
		
		<dc:creator><![CDATA[Grab Tech]]></dc:creator>
		<pubDate>Fri, 25 Sep 2026 00:00:00 +0000</pubDate>
				<category><![CDATA[artificial intelligence]]></category>
		<category><![CDATA[Engineering]]></category>
		<category><![CDATA[LLM]]></category>
		<guid isPermaLink="false">https://engineering.grab.com/automated-merchant-review-summary-system-with-integrated-feedback</guid>

					<description><![CDATA[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 s...]]></description>
		
		
		
			</item>
		<item>
		<title>Data Mesh at Grab (Part III): Operationalizing data reliability with automated DPIs</title>
		<link>https://noise.getoto.net/2026/08/28/data-mesh-at-grab-part-iii-operationalizing-data-reliability-with-automated-dpis/</link>
		
		<dc:creator><![CDATA[Grab Tech]]></dc:creator>
		<pubDate>Fri, 28 Aug 2026 00:00:00 +0000</pubDate>
				<category><![CDATA[data]]></category>
		<category><![CDATA[Data Quality]]></category>
		<category><![CDATA[database]]></category>
		<category><![CDATA[Engineering]]></category>
		<category><![CDATA[observability]]></category>
		<guid isPermaLink="false">https://engineering.grab.com/data-mesh-at-grab-part-three</guid>

					<description><![CDATA[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 t...]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>Building Jarvis Pro: Route first, answer later</title>
		<link>https://noise.getoto.net/2026/08/21/building-jarvis-pro-route-first-answer-later/</link>
		
		<dc:creator><![CDATA[Grab Tech]]></dc:creator>
		<pubDate>Fri, 21 Aug 2026 00:00:00 +0000</pubDate>
				<category><![CDATA[Account management]]></category>
		<category><![CDATA[artificial intelligence]]></category>
		<category><![CDATA[Engineering]]></category>
		<category><![CDATA[Product]]></category>
		<guid isPermaLink="false">https://engineering.grab.com/jarvis-pro-route-firsr-answer-later</guid>

					<description><![CDATA[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 w...]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>Grab Bench: Evaluating AI on Grab-shaped production work</title>
		<link>https://noise.getoto.net/2026/08/12/grab-bench-evaluating-ai-on-grab-shaped-production-work/</link>
		
		<dc:creator><![CDATA[Grab Tech]]></dc:creator>
		<pubDate>Wed, 12 Aug 2026 00:00:00 +0000</pubDate>
				<category><![CDATA[artificial intelligence]]></category>
		<category><![CDATA[Engineering]]></category>
		<category><![CDATA[machine learning]]></category>
		<category><![CDATA[Product]]></category>
		<guid isPermaLink="false">https://engineering.grab.com/grab-bench-evaluating-ai</guid>

					<description><![CDATA[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 ...]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>How AI is transforming analytics at Grab</title>
		<link>https://noise.getoto.net/2026/08/01/how-ai-is-transforming-analytics-at-grab-2/</link>
		
		<dc:creator><![CDATA[Grab Tech]]></dc:creator>
		<pubDate>Sat, 01 Aug 2026 00:23:00 +0000</pubDate>
				<category><![CDATA[AI]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[Engineering]]></category>
		<guid isPermaLink="false">https://engineering.grab.com/how-ai-is-transforming-analytics</guid>

					<description><![CDATA[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,...]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>Crowdsourced taxonomy verification: A feedback-driven framework for refining knowledge graph relationships via online search interactions</title>
		<link>https://noise.getoto.net/2026/07/30/crowdsourced-taxonomy-verification-a-feedback-driven-framework-for-refining-knowledge-graph-relationships-via-online-search-interactions/</link>
		
		<dc:creator><![CDATA[Grab Tech]]></dc:creator>
		<pubDate>Thu, 30 Jul 2026 00:00:00 +0000</pubDate>
				<category><![CDATA[data]]></category>
		<category><![CDATA[Engineering]]></category>
		<category><![CDATA[graphs]]></category>
		<category><![CDATA[LLM]]></category>
		<category><![CDATA[machine learning]]></category>
		<category><![CDATA[Search]]></category>
		<guid isPermaLink="false">https://engineering.grab.com/crowdsourced-taxonomy-verification</guid>

					<description><![CDATA[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 rapid...]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>Agent platform (Part 1): How we help Grab build and run AI agents at scale</title>
		<link>https://noise.getoto.net/2026/07/24/agent-platform-part-1-how-we-help-grab-build-and-run-ai-agents-at-scale/</link>
		
		<dc:creator><![CDATA[Grab Tech]]></dc:creator>
		<pubDate>Fri, 24 Jul 2026 00:00:10 +0000</pubDate>
				<category><![CDATA[design]]></category>
		<category><![CDATA[Engineering]]></category>
		<category><![CDATA[Experiment]]></category>
		<category><![CDATA[generative AI]]></category>
		<category><![CDATA[LLM]]></category>
		<category><![CDATA[machine learning]]></category>
		<guid isPermaLink="false">https://engineering.grab.com/how-grab-builds-and-runs-ai-agents-at-scale</guid>

					<description><![CDATA[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 ag...]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>Scaling Grab&#8217;s Data Lake: Our journey to Apache Iceberg adoption</title>
		<link>https://noise.getoto.net/2026/07/10/scaling-grabs-data-lake-our-journey-to-apache-iceberg-adoption/</link>
		
		<dc:creator><![CDATA[Grab Tech]]></dc:creator>
		<pubDate>Fri, 10 Jul 2026 00:00:00 +0000</pubDate>
				<category><![CDATA[Apache Iceberg]]></category>
		<category><![CDATA[data]]></category>
		<category><![CDATA[database]]></category>
		<category><![CDATA[Engineering]]></category>
		<category><![CDATA[Spark]]></category>
		<guid isPermaLink="false">https://engineering.grab.com/our-journey-to-apache-iceberg-adoption</guid>

					<description><![CDATA[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 mode...]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>Migrating Counter Service storage: Design choices and learnings</title>
		<link>https://noise.getoto.net/2026/07/03/migrating-counter-service-storage-design-choices-and-learnings/</link>
		
		<dc:creator><![CDATA[Grab Tech]]></dc:creator>
		<pubDate>Fri, 03 Jul 2026 00:00:00 +0000</pubDate>
				<category><![CDATA[artificial intelligence]]></category>
		<category><![CDATA[DevSecOps]]></category>
		<category><![CDATA[Engineering]]></category>
		<category><![CDATA[Kubernetes]]></category>
		<category><![CDATA[Platform]]></category>
		<category><![CDATA[security]]></category>
		<guid isPermaLink="false">https://engineering.grab.com/counter-service-storage-migration</guid>

					<description><![CDATA[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 (Q...]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>Palana (Part 2): Architecting isolation, identity, and auditability for AI agents</title>
		<link>https://noise.getoto.net/2026/06/21/palana-part-2-architecting-isolation-identity-and-auditability-for-ai-agents/</link>
		
		<dc:creator><![CDATA[Grab Tech]]></dc:creator>
		<pubDate>Sun, 21 Jun 2026 00:00:00 +0000</pubDate>
				<category><![CDATA[artificial intelligence]]></category>
		<category><![CDATA[DevSecOps]]></category>
		<category><![CDATA[Engineering]]></category>
		<category><![CDATA[Kubernetes]]></category>
		<category><![CDATA[Platform]]></category>
		<category><![CDATA[security]]></category>
		<guid isPermaLink="false">https://engineering.grab.com/part-2-palana-architecture</guid>

					<description><![CDATA[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 uni...]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>Palana (Part 1): Why Grab built a secure platform for autonomous AI Agents</title>
		<link>https://noise.getoto.net/2026/06/19/palana-part-1-why-grab-built-a-secure-platform-for-autonomous-ai-agents/</link>
		
		<dc:creator><![CDATA[Grab Tech]]></dc:creator>
		<pubDate>Fri, 19 Jun 2026 00:00:00 +0000</pubDate>
				<category><![CDATA[artificial intelligence]]></category>
		<category><![CDATA[DevSecOps]]></category>
		<category><![CDATA[Engineering]]></category>
		<category><![CDATA[Kubernetes]]></category>
		<category><![CDATA[Platform]]></category>
		<category><![CDATA[security]]></category>
		<guid isPermaLink="false">https://engineering.grab.com/palana-part-1-secure-platform-for-ai-agents</guid>

					<description><![CDATA[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-ru...]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>Scaling out Distroless adoption with AI</title>
		<link>https://noise.getoto.net/2026/06/12/scaling-out-distroless-adoption-with-ai/</link>
		
		<dc:creator><![CDATA[Grab Tech]]></dc:creator>
		<pubDate>Fri, 12 Jun 2026 00:00:00 +0000</pubDate>
				<category><![CDATA[artificial intelligence]]></category>
		<category><![CDATA[Containers]]></category>
		<category><![CDATA[DevSecOps]]></category>
		<category><![CDATA[Engineering]]></category>
		<category><![CDATA[security]]></category>
		<guid isPermaLink="false">https://engineering.grab.com/scaling-out-distroless-adoption-with-ai</guid>

					<description><![CDATA[Introduction

Grab is migrating from heavy base images like Ubuntu to Distroless images to reduce security risks. By stripping containers down to the bare application and its runtime, we eliminate unnecessary binaries and Common Vulnerabilities and Exp...]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>From decentralized Docs-as-Code to a centralized repository: Evolving Grab&#8217;s documentation strategy</title>
		<link>https://noise.getoto.net/2026/05/29/from-decentralized-docs-as-code-to-a-centralized-repository-evolving-grabs-documentation-strategy/</link>
		
		<dc:creator><![CDATA[Grab Tech]]></dc:creator>
		<pubDate>Fri, 29 May 2026 00:00:00 +0000</pubDate>
				<category><![CDATA[blog]]></category>
		<category><![CDATA[Engineering]]></category>
		<category><![CDATA[Helix]]></category>
		<category><![CDATA[TechDocs]]></category>
		<guid isPermaLink="false">https://engineering.grab.com/evolving-documentation-strategy</guid>

					<description><![CDATA[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 oth...]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>The Hugo evolution: Engineering Grab&#8217;s unified, one-click data ingestion platform with Apache Flink</title>
		<link>https://noise.getoto.net/2026/05/22/the-hugo-evolution-engineering-grabs-unified-one-click-data-ingestion-platform-with-apache-flink/</link>
		
		<dc:creator><![CDATA[Grab Tech]]></dc:creator>
		<pubDate>Fri, 22 May 2026 00:23:00 +0000</pubDate>
				<category><![CDATA[data]]></category>
		<category><![CDATA[database]]></category>
		<category><![CDATA[Engineering]]></category>
		<category><![CDATA[FlinkSQL]]></category>
		<category><![CDATA[Hugo]]></category>
		<guid isPermaLink="false">https://engineering.grab.com/one-click-data-ingestion-platform-with-apache-flink</guid>

					<description><![CDATA[Introduction

Data drives every decision we make at Grab. As our operations scale, so does our need for robust, real-time data ingestion and processing frameworks. Enter Hugo: our self-service data platform that has long empowered teams to seamlessly r...]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>How AI is transforming analytics at Grab</title>
		<link>https://noise.getoto.net/2026/05/15/how-ai-is-transforming-analytics-at-grab/</link>
		
		<dc:creator><![CDATA[Grab Tech]]></dc:creator>
		<pubDate>Fri, 15 May 2026 00:23:00 +0000</pubDate>
				<category><![CDATA[AI]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[Engineering]]></category>
		<guid isPermaLink="false">https://engineering.grab.com/how-ai-is-transforming-analytics-at-grab.md</guid>

					<description><![CDATA[Introduction

At Grab, analytics sits close to almost every decision that matters. Our north star is the democratization of intelligence, ensuring that anyone making a business call has immediate access to trustworthy answers.

Over the last two years,...]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>Scaling developer experience: How we improved Android Studio in a large monorepo</title>
		<link>https://noise.getoto.net/2026/05/15/scaling-developer-experience-how-we-improved-android-studio-in-a-large-monorepo/</link>
		
		<dc:creator><![CDATA[Grab Tech]]></dc:creator>
		<pubDate>Fri, 15 May 2026 00:23:00 +0000</pubDate>
				<category><![CDATA[Android]]></category>
		<category><![CDATA[Engineering]]></category>
		<category><![CDATA[monorepo]]></category>
		<category><![CDATA[Performance]]></category>
		<guid isPermaLink="false">https://engineering.grab.com/how-we-improved-android-studio-in-large-monorepo</guid>

					<description><![CDATA[Introduction

Long integrated development environment (IDE) sync/indexing times can quietly erode developer productivity, making code navigation sluggish, spiking memory usage, and slowing down Jetpack Compose preview updates, turning the IDE into a bo...]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
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