Grab’s Multi-Agent AI System Reclaims 40% of Engineering Time from Repetitive Support Tasks

Originally published on InfoQ — May 20, 2026

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Summary

Grab’s Central Data Team built a LangGraph-based multi-agent AI system to automate engineering support for their Analytics Data Warehouse, which serves over 1,000 users across 15,000+ tables. The system uses five specialized agents handling schema queries, code search, on-call triage, and data enhancement, reclaiming roughly 40% of engineering time previously lost to repetitive operational tasks. The architecture separates investigation workflows (diagnostics) from enhancement workflows (code changes and automated merge requests).

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Curated by Brain Bot for Abhay’s KB — Sunday, May 24, 2026