Vectara's models

Vectara's models

Vectara's advanced end-to-end RAG models have pioneered enterprise-grade RAG.

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Best-of-breed models at every stage

A RAG pipeline is only as good as the models that power it.

So we maintain state-of-the-art models for every step in the process.

Multilingual semantic search

See announcement

Boomerang manages retrieval in RAG, grounding results in datasets and supporting Hybrid Search by mapping concepts to vectors, not keywords.

Boomerang supports hundreds of languages and dialects and uses zero-shot learning to quickly find relevant information across diverse domains.

Boomerang’s performance benchmarks

Performance details (June 2024)

Reranking for relevance and variety

See documentation

The Slingshot model reorganizes search results to ensure relevance and avoid redundancy, delivering accurate outcomes across queries.

It can be combined with inputs based on your priorities, such as recency or keyword frequency, to ensure the most relevant information rises to the top.

Slingshot’s performance benchmarks

Performance details (May 2024)

Context-aware multilingual generation

Explore documentation

The Mockingbird LLM is the “G” in our RAG platform. We’ve optimized it to deliver highly relevant answers and cite sources for each claim.

Mockingbird handles queries and results from diverse domains and languages. It can generate everything modern AI applications need.

Mockingbird’s performance benchmarks

Performance details (July 2024)

Hallucination detection for any LLM

View documentation

The Hughes Hallucination Evaluation Model assesses LLMs for hallucinated results versus factual consistency.

The free version is on Hugging Face, with a more advanced version used in our platform's Factual Consistency Score.

Our Hallucination Evaluation Model is a first-of-its-kind initiative to proffer a commercially available and open-source model that addresses the accuracy and level of hallucination in LLMs.

Simon Hughes (1979 – 2023) – ML Engineer & AI Researcher Vectara

HHEM’s hallucination detection performance benchmarks

Performance details (August 2024)

Remembering a champion of responsible AI

The Hughes Hallucination Evaluation Model honors Dr. Simon Mark Hughes, a pioneering machine learning engineer at Vectara. His research on AI hallucination detection, before his passing in 2023, continues to shape industry efforts toward truthful and reliable AI outputs.

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