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Engineering · Data Analytics · Data Science
Streamlining 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. -
Engineering · Data Analytics · Data Science
Introducing 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. -
Engineering · Data Analytics
Improving 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. -
Engineering · Data Analytics
Building 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.