# How Vinted Serves Personalised Search Autocomplete

DevFeed: [How Vinted Serves Personalised Search Autocomplete](<https://devfeed.tech/articles/how-vinted-serves-personalised-search-autocomplete-20447.md>)

Original publisher: [Read original article](<https://vinted.engineering//2026/04/22/personalized-search-autocomplete/>)

Author: Justina Bartulevičienė

Published: 2026-04-22T00:00:00Z

Content type: article

Language: en

Sources: [Vinted](<https://devfeed.tech/sources/vinted.md>)

Topics: [recommendation systems](<https://devfeed.tech/topics/recommendation-systems.md>), [data](<https://devfeed.tech/topics/data.md>), [systems](<https://devfeed.tech/topics/systems.md>), [Learning](<https://devfeed.tech/topics/learning.md>)

Tags: [autocomplete](<https://devfeed.tech/tags/autocomplete.md>), [model](<https://devfeed.tech/tags/model.md>), [offline](<https://devfeed.tech/tags/offline.md>), [performance](<https://devfeed.tech/tags/performance.md>), [personalisation](<https://devfeed.tech/tags/personalisation.md>), [pipeline](<https://devfeed.tech/tags/pipeline.md>), [search](<https://devfeed.tech/tags/search.md>)

## AI overview

Vinted describes the architecture and operation of its personalized search autocomplete service. The system generates candidate queries from product metadata and search logs, indexes and matches them with typo tolerance, and ranks suggestions using personalization and a Learning-to-Rank model. The service supports 24 languages and more than 50 country-language combinations, with 125 million queries and reported throughput of 4,700 queries per second at 31 ms P99.

## Source excerpt

At Vinted, more than 20% of all search sessions now start with a click on an autocomplete suggestion. A few years ago, that number was below 8%. Autocomplete not only saves typing effort - it helps people discover listings they didn't know existed, and guides them toward successful searches. Today, across 24 languages and 50+ country-language combinations, we have a pool of 125 million different queries ready to suggest to users. Our service, svc-suggestions, runs on Vespa and matches and ranks 4,700 queries per second at 31 ms P99.