Vectara for retrieval

Vectara’s Boomerang model provides unrivaled accuracy and relevance across languages.

Accurate and relevant retrieval is often an afterthought

You can spend months building complex systems with LLMs and vector databases, only to end up with an AI agent that hallucinates and gives wrong answers. Instead, you could use Vectara for accurate retrieval without the hassle.

Getting agents to operate correctly in production involves combining complex components in the right way. Vectara has proven the platform can do this well especially when multimodal data is involved.

Alan Davidson

Chief Information Officer, Broadcom

Industry-leading retrieval right out-of-the-box

Superior information retrieval means answers are precise, accurate, and relevant. Vectara’s retrieval model is among the best in the world.

Leveraging Hybrid Search, it provides the most pertinent answer regardless of a query’s length, level of ambiguity, language, or provided context.

Vectara gives users ultimate control to dial in the desired levels of semantic or keyword search for your specific use case.

Backed by Guardian Agents

Vectara provides a suite of guardian agents to ensure retrieval remains high-fidelity throughout.

Hybrid Search (semantic + keyword)

Vectara uses hybrid search, combining LLM-based retrieval and keyword match to find the most relevant products, support cases, and documents.

Superior cross-language retrieval

Vectara supports cross-language search for over 100 languages.

That means your users can search in one language for content written in another.

All of this happens automatically in Vectara. There’s no need to set up manual third-party translation, custom NLP rules, or a litany of synonyms that map words and concepts.

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