Swiggy Improves Search Autocomplete Using Real Time Machine Learning Ranking

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Posted on Mon May 18 2026 | 8:08 pm

Swiggy detailed real-time machine-learning ranking system for autocomplete built on OpenSearch. The architecture separates candidate generation and ranking, uses feature stores for real time signals, and applies learning to rank models for improved relevance. It replaces heuristic ranking while maintaining strict latency constraints and enabling continuous model updates from user behavior signals.

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