How Query Quotient built a resilient OpenSearch infrastructure that powers fast job matching for millions of users across Southeast Asia's most diverse job markets.
GrabJobs, Southeast Asia's fastest-growing job portal, was facing critical scalability challenges as it expanded across multiple countries. Its search infrastructure couldn't keep pace with growth:
Supporting 12+ languages - including Thai, Vietnamese, Bahasa and Chinese - with accurate results was not possible on the existing setup.
Processing 500,000+ new job listings daily caused severe indexing delays and inconsistent search results.
Matching candidates to jobs required algorithms that consider skills, location, salary and cultural fit.
Unoptimized infrastructure was consuming 70% of the technology budget while still underperforming.
We designed and implemented an OpenSearch solution tailored to GrabJobs' multi-market, multi-language requirements.
A search system built for Southeast Asia's linguistic diversity:
A distributed indexing system built for heavy write loads:
Matching that goes beyond keyword search:
Infrastructure redesigned for efficiency:
Analysis of existing infrastructure and requirements gathering.
Multi-language search architecture and infrastructure planning.
Building and deploying the new OpenSearch infrastructure.
Zero-downtime migration and performance tuning.
The OpenSearch platform delivered results on both the technical and the business side:
“Query Quotient didn't just solve our search problems – they transformed how we think about connecting job seekers with opportunities. The multi-language capabilities and lightning-fast performance have been instrumental in our expansion across Southeast Asia. We've seen a 250% increase in successful job matches since the implementation.”
Cross-lingual retrieval, ML-based skill extraction and behavior-based ranking are the same building blocks behind semantic search and AI-driven matching. A fast, multilingual retrieval layer is what lets those features work at 10M+ listings.
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