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Engineering · DataHow we built a custom vision LLM to improve document processing at Grab
e-KYC faces challenges with unstandardized document formats and local SEA languages. Existing LLMs lack sufficient SEA language support. We trained a Vision LLM from scratch, modifying open-source models to be 50% faster while maintaining accuracy. These models now serve live production traffic across Grab's ecosystem for merchant, driver, and user onboarding.
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Engineering · DataMachine-learning predictive autoscaling for Flink
Explore how Grab uses machine learning to perform predictive scaling on our data processing workloads.
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Engineering · DataModernising Grab’s model serving platform with NVIDIA Triton Inference Server
Dive into Grab’s engineering journey to optimise a core ML model. Learn how we built the Triton Server Manager and used Triton Inference Server (TIS) to achieve a 50% reduction in tail latency and seamlessly migrate over 50% of online deployments.
