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Documentation Index

Fetch the complete documentation index at: https://docs.siray.ai/llms.txt

Use this file to discover all available pages before exploring further.

Model Use Cases

Best for semantic search, document similarity, intent classification, and lightweight RAG pipelines where low latency and cost efficiency are critical.

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Key Features

  • Fast Embedding Generation: Optimized for low latency, enabling real-time semantic search and ranking in high-traffic applications.
  • Cost-Efficient at Scale: Designed for large-volume embedding workloads with minimal cost while maintaining strong semantic accuracy.
  • Semantic Similarity Accuracy: Produces reliable vector representations for clustering, deduplication, and relevance scoring.
  • RAG-Ready Output: Works seamlessly with vector databases for retrieval-augmented generation pipelines.

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