Embedding API

An embedding API is a network endpoint that converts text or other modal input into embedding vectors via a remote model service, the most common pattern for accessing embedding models in production. Major embedding APIs include OpenAI Embeddings (text-embedding-3-small and -large), Cohere Embed v3, Voyage AI, Google Vertex AI Text Embeddings, AWS Bedrock embeddings, Azure OpenAI Embeddings, and the Hugging Face Inference API. Pricing is typically per-token (OpenAI, Cohere) or per-request (Voyage, some self-hosted services), with substantial cost differences across providers — text-embedding-3-small is $0.02 per million tokens, while text-embedding-3-large is $0.13 per million. AI governance teams use embedding APIs through governed gateways that meter usage, enforce per-skill or per-tenant budgets, and produce audit logs for AI compliance. Self-hosted embedding services through vLLM, Text Embeddings Inference (TEI), or Hugging Face Inference Endpoints provide alternatives for AI compliance scenarios that prohibit sending text to external APIs. The choice between hosted and self-hosted embedding APIs is one of the most consequential cost-versus-control decisions in RAG architecture.

Embedding API governance through Centralpoint: Centralpoint sits in front of every embedding API your enterprise uses — OpenAI, Cohere, Voyage, AWS Bedrock, on-prem TEI — metering tokens, logging requests, and enforcing per-skill budgets. The model-agnostic platform keeps prompts on-premise, supports both generative and embedded models, and deploys chatbots through one line of JavaScript with audit-ready governance.


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