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EngineeringFrom failure to success: The birth of GrabGPT, Grab’s internal ChatGPT
When Grab's Machine Learning team sought to automate support queries, a failed chatbot experiment sparked an unexpected pivot: GrabGPT. Born from the need to harness Large Language Models (LLMs) internally, this tool became a go-to resource for employees. Offering private, auditable access to models like GPT and Gemini, the author shares his journey of turning failed experiments into strategic wins.
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Engineering · Data Analytics · Data ScienceStreamlining RiskOps with the SOP agent framework
Discover how the SOP-driven Large Language Model (LLM) agent framework is revolutionising Risk Operations (RiskOps) by automating Account Takeover (ATO) investigations. Explore the potential of this transformative tool to unlock unprecedented levels of productivity and innovation across industries.
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Engineering · Data Analytics · Data ScienceIntroducing the SOP-driven LLM agent frameworks
The SOP-driven Large Language Model (LLM) agent framework, revolutionises enterprise AI by integrating Standard Operating Procedures (SOPs) to ensure reliable execution and boost productivity. Achieving over 99.8% accuracy, it offers versatile automation tools and app development, making AI solutions 10 times faster. The framework addresses LLM challenges by structuring SOPs as a tree, enabling intuitive workflow creation. The framework aims to transform enterprise operations and explore industry applications.
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EngineeringEvaluating performance impact of removing Redis-cache from a Scylla-backed service
At Grab, we recently reevaluated a setup that combined Scylla with an external Redis cache. We decided to remove Redis and adjusted our Scylla configurations and strategies accordingly. This change helped reduce latency spikes while significantly lowering the overall cost. In this article, we explore the process, the challenges we faced, and the solutions we implemented to create a more efficient and cost-effective setup.
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EngineeringFacilitating Docs-as-Code implementation for users unfamiliar with Markdown
In this article, we'll discuss how we've streamlined the Docs-as-Code process for technical contributors, specifically engineers, who are already familiar with GitLab but might face challenges with Markdown. Discover how we plan to improve the workflow for non-engineering teams contributing to service and standalone documentation.
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Engineering · Data AnalyticsImproving Hugo stability and addressing oncall challenges through automation
Managing 4,000+ data pipelines demanded a smarter approach to stability. We built a comprehensive automation solution that enhances Hugo's monitoring capabilities, streamlines issue diagnosis, and significantly reduces on-call workload. Explore our architecture, implementation, and the impact of automated healing features.
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Engineering · Data AnalyticsBuilding a Spark observability product with StarRocks: Real-time and historical performance analysis
Discover how Grab revolutionised its Spark observability with StarRocks! We transformed our monitoring capabilities by moving from a fragmented system to a unified, high-performance platform. Learn about our journey from the initial Iris tool to a robust solution that tackles limitations with real-time and historical data analysis, all powered by StarRocks. Explore the architecture, data model, and advanced analytics that enable us to provide deeper insights and recommendations for optimising Spark jobs at Grab.
Engineering
Effortless enterprise authentication at Grab: Dex in action
This article outlines Grab's journey towards enabling a seamless single sign-on experience for its numerous internal applications. It addresses the challenges of fragmented authentication and authorisation systems and introduces Dex, an open-source federated OpenID Connect provider, as the chosen solution. The document details the implementation of Dex, its key features, and discusses future plans for an unified authorisation model.
