One API for every model — and tool

Embeddings through the same API as everything else.

Search, RAG, and clustering all start with embeddings. VernaOne generates them through the same project-scoped API and provider routing as your models — so your retrieval layer shares the keys, governance, and analytics as the rest of your AI stack.

Try VernaOne free → ← All features

~15 providers & tools behind one API — LLMs, media, search & scraping

OpenAIAnthropic ClaudeGoogle GeminiMeta LlamaOpenRouter

Embeddings usually live in their own silo

Embedding generation often ends up as yet another provider integration, with its own key management and its own place in the codebase, disconnected from how you govern generation. That fragments keys, cost tracking, and provider choice.

Switching embedding providers later means touching a separate integration.

How embeddings work in VernaOne

  1. 1

    One project-scoped API

    Create embeddings through the same API, keyed to your project — the same surface you use for text and media.

  2. 2

    Provider routing

    Route embeddings through your chosen provider under the same bring-your-own-key accounts, so keys and billing stay unified.

  3. 3

    Feed search, RAG & clustering

    Use the vectors for semantic search, retrieval-augmented generation, and clustering — with generation living right next door in the same platform.

  4. 4

    Unified governance

    Embeddings run under the same projects, keys, and analytics as everything else.

Highlights

🧮

Same project-scoped API

Embeddings on the same surface as text and media — one integration.

🔑

Unified keys

Bring-your-own-key accounts and billing cover embeddings too.

🔎

Search, RAG, clustering

Vectors ready for retrieval and grouping, next to your generation prompts.

📊

One analytics view

Embedding usage tracked alongside the rest of your AI spend.

Retrieval and generation share the same keys, provider routing, and analytics — your RAG stack stops being a separate silo.

Ship on this — free to start.

Author a prompt once and call it by name. VernaOne handles the model, the fallback, the cost, and the alerting.

Launch VernaOne →

Frequently asked

What can I use VernaOne embeddings for?

Semantic search, retrieval-augmented generation (RAG), and clustering — the vectors are generated through the same project-scoped API and provider routing as your models.

Do embeddings use my own provider keys?

Yes. Embeddings run under the same bring-your-own-key provider accounts as text and media, so keys, billing, and provider choice stay unified.