Can Haystack be used for real-time multilingual AI search?

All answers to this question.

Are you planning to host this on-prem or in the cloud? If you use a hosted service like Azure or AWS, they have native multilingual models that integrate easily via Haystack’s WebRetriever nodes.

   Answered 2025-05-12 by Patrick Hughes

• Patrick, we are leaning towards a private cloud deployment on AWS. I was looking into using the Amazon Bedrock integration with Haystack. My main concern is cost—do you think the token usage for multilingual embeddings is significantly higher than English-only models, or is it comparable? I want to keep our operational costs predictable as we scale to more users.

     Commented 2025-05-14 by Larry Jenkins

I've had great success with the Sentence Transformers integration in Haystack. It handles the multilingual mapping very smoothly without needing extra translation layers.

   Answered 2025-05-16 by Sharon Ross

• SentenceTransformersDocumentEmbedder is very straightforward to set up and works like a charm for cross-language retrieval tasks.

     Commented 2025-05-17 by Cynthia Barnes

Yes, Haystack is excellent for multilingual setups. Using a multilingual embedding model is generally much better than translating queries because it preserves the semantic intent across languages without the overhead of a translation API. We recently deployed a system using the MultilingualDPR retriever in Haystack for a global client. One tip: make sure your DocumentStore is configured to handle UTF-8 characters properly. Also, if you want even higher precision, you can add a LanguageClassifier node at the start of your pipeline to route queries to language-specific re-rankers. This approach significantly outperformed our old "translate-then-search" method.

   Answered 2025-11-12 by Melissa Wagner