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Text Embeddings

Embedding models convert text into numbers that capture meaning — the foundation for smart search, “find similar,” and retrieval features inside the tools your team builds.

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What it’s good at

  • Meaning-aware search
  • Great for retrieval
  • Fast and inexpensive

Popular uses

  • Semantic search over documents
  • Recommendations
  • Powering AI assistants with your own data

How your team uses Text Embeddings

It’s available to everyone on your Roar account the moment you sign up — no separate subscription, no waiting. Non-technical teammates use it through the tools they build; developers call it directly by its model name text-embed-large — with cost routing and failover handled automatically.

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