Vectara’s industry-leading Relevance (the “R” in RAGaaS), simple and powerful APIs, and offloading many components in the GenAI pipeline to accelerate development are why developers who’ve built their own come back to Vectara. Vectara never trains on your data, allowing businesses to embed generative AI capabilities without the risk of data or privacy violations.
REASON #1
Best-in-Class Retrieval & Hybrid Search
Retrieval is THE most important component in any RAG system (e.g., garbage in = garbage out). That’s why Vectara’s founders, early members of Google’s Research team, focused on building a world-class retrieval model from the very beginning, which we now call “Boomerang.” Additionally, the Vectara platform’s flexibility allows the use of multiple best-fit LLMs for search, retrieval, and summarization.
REASON #2
Retrieval Augmented Generation-as-a-Service (RAGaaS)
Some LLMs train their models on your data. Some hallucinate when they don’t know the answers to your questions. And some lexical searches provide more relevant answers than solely semantic searches. Retrieval Augmented Generation (RAG) remedies all of this.
Our summarization is grounded in the facts retrieved (by Boomerang) from the indexed data. This means that we significantly reduce the probability of hallucination during the summarization stage; we provide an answer which is concise and sound based on the intended meaning vs. rephrasing the underlying data. With Vectara’s RAGaaS you can ensure your results are in context and hallucinations are all but eliminated.
REASON #3
End-to-End Platform
Vectara provides a complete GenAI experience from extraction, encoding, and indexing to retrieval and rerank. Vectara automatically routes data across relevant backend services to deliver supporting services from snippet extraction to calibration with a single, unified API. The platform is self-optimizing; it automatically fine-tunes the neural network hyperparameters to achieve and maintain optimized outcomes for each indexed data set.
REASON #4
Ease of Use
Vectara’s powerful end-to-end platform is self-optimizing and easily consumed via simple APIs, getting businesses up and running in just a few minutes and without requiring the addition of any specialized engineers or infrastructure.
REASON #5
Superior Cross-language Understanding
Vectara supports cross-language search and retrieval, the ability to search in one language for content written in another language. All of this happens automatically in Vectara: there’s no need to set up manual 3rd party translation, custom NLP rules for different languages, or a litany of synonyms that map words and concepts, all of which can be the requirement to handle cross-lingual content and users in many other systems.
