Supercharging
Search
and
Retrieval
for Unstructured
Data
Best-in-class embedding models and rerankers
Embeddings and Rerankers Drive RAG Retrieval and Response Quality

Unstructured data



Embedding model



Vector DB



Reranker



Relevant files



LLM



Factual responses with lower costs
A Spectrum of Models for Your Target Use Cases
General-purpose models
Ready for any purpose and language out-of-the-box.
Domain-specific models
Highly optimized for industry-specific data, like finance, legal, and code.
Company-specific models
Fine-tuned librarians for your company’s unique data and lingo.

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High accuracy
Retrieving the most relevant contextual information

Low dimensionality
3x-8x shorter vectors ⇒ cheaper vector search and storage

Low latency
4x smaller model and faster inference with superior accuracy

Cost efficient
2x cheaper inference with superior accuracy

Long-context
Longest commercial context length available (32K tokens)

Modularity
Plug-and-play with any vectorDB and LLM



















