AI API for semantic search and reranking

Here are good AI API options for semantic search and reranking, depending on whether you want one provider or a mix-and-match setup.

Common architecture

1. Embed documents/query with an embeddings API
2. Retrieve top-k candidates via vector search
3. Rerank those candidates with a reranking model
4. Return final results

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Popular API options

1) OpenAI

• Embeddings: text-embedding-3-small, text-embedding-3-large
• Reranking: no dedicated standalone rerank API, but you can use an LLM to score relevance or do pairwise ranking
• Good for:
  • high-quality embeddings
  • simple integration if you already use OpenAI
• Best when:
  • you want a single vendor for semantic representation
  • you can implement reranking yourself with an LLM prompt

2) Cohere

• Embeddings: yes
• Rerank: yes, Cohere is especially known for its rerank endpoint
• Good for:
  • semantic search + built-in reranking
  • strong retrieval use cases
• Best when:
  • you want an out-of-the-box reranker

3) Voyage AI

• Embeddings: yes
• Reranking: yes
• Good for:
  • retrieval/search quality
  • modern embedding + rerank stack
• Best when:
  • you care a lot about search relevance quality

4) Google Vertex AI / Gemini

• Embeddings: yes
• Reranking: some retrieval/ranking support via Vertex AI Search and custom models
• Good for:
  • enterprise integration
  • GCP-native search pipelines

5) Azure AI Search + Azure OpenAI

• Embeddings: via Azure OpenAI
• Reranking: Azure AI Search supports semantic ranking features
• Good for:
  • managed search infrastructure
  • enterprise search apps

6) Anthropic / LLM-based reranking

• No dedicated embeddings/rerank service in the classic sense
• You can use the model to judge relevance or compare results
• Good for:
  • custom logic
  • smaller candidate sets

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If you want the best practical setup

Recommended stack

• Embeddings: OpenAI / Cohere / Voyage
• Vector DB: Pinecone, Weaviate, Qdrant, pgvector, Elasticsearch, OpenSearch
• Reranker: Cohere Rerank or Voyage Rerank

This is a very common production pattern.

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Quick selection guide

• Best dedicated reranker: Cohere
• Best overall semantic search stack: Cohere or Voyage
• Best if already using OpenAI: OpenAI embeddings + your own reranker
• Best enterprise cloud-native: Azure AI Search / Vertex AI

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Example workflow

1. User asks: “best laptop for software development under $1500”
2. Embed query
3. Retrieve top 50 docs from vector DB
4. Rerank top 50 with rerank API
5. Return top 5 results

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If you want, I can also provide:

• a comparison table of providers
• sample API calls in Python/JavaScript
• a recommended stack by budget
• help choosing between Cohere vs OpenAI vs Voyage