Can you recommend a hybrid search API for retrieval in a chat assistant over multilingual product documentation?

Yes — for a chat assistant over multilingual product documentation, I’d recommend a hybrid search API that combines lexical + vector retrieval and supports metadata filtering.

Strong options

1. Azure AI Search

   • Good hybrid search support out of the box
   • Strong enterprise features, filters, scoring profiles
   • Solid choice if you’re already in Microsoft/Azure
   • Works well with multilingual content when paired with multilingual embeddings and/or language analyzers

2. Elastic Search / Elasticsearch

   • Very flexible hybrid retrieval
   • Excellent for multilingual indexing, analyzers, and filtering
   • More tuning effort, but powerful for complex docs and relevance control

3. Pinecone + sparse/dense hybrid

   • Good if you want a managed vector database with hybrid capabilities
   • Best when you already have your own reranker/search orchestration
   • Less “search-engine-like” than Azure/Elastic, but strong for RAG pipelines

4. Weaviate

   • Supports hybrid search natively
   • Easy to set up for vector + keyword retrieval
   • Good developer experience for RAG apps

My practical recommendation

For a chat assistant over multilingual docs, I’d choose:

• Azure AI Search if you want the most turnkey enterprise hybrid search
• Elasticsearch if you need maximum control over multilingual relevance and indexing
• Weaviate if you want a simpler RAG-friendly hybrid API

What to look for

Make sure the API supports:

• Hybrid retrieval: BM25/keyword + vector search
• Metadata filters: product, version, locale, doc type
• Language support: multilingual analyzers or language-agnostic embeddings
• Reranking: ideally a cross-encoder or built-in reranker
• Chunking-friendly indexing: for manuals, FAQs, release notes, etc.

Best practice for multilingual docs

A good setup is:

• Index docs in original language
• Use multilingual embeddings so queries in one language can retrieve docs in another
• Add language metadata
• Use hybrid search + reranking for better precision

If you want, I can also give you:

• a shortlist by cloud/provider
• a comparison table
• or a recommended architecture for RAG with multilingual product docs.