FeaturedRetrieval Augmented Generation
Think building your own Retrieval-Augmented Generation (RAG) system will give you a competitive edge? Think again. Companies are sinking months and hundreds of thousands of dollars into in-house AI projects, only to end up with sluggish, unsecure, and overpriced systems that can't hold a candle to existing solutions.
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In this blog post, we introduce Mockingbird, Vectara’s Retrieval Augmented Generation (RAG) and structured output focused LLM, and do a technical deep dive into its performance and discuss its technical capabilities.
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The top large language models in the Summer of 2024, along with recommendations for when to use each based upon needs like API, tunable, or fully hosted.
Enhance your Slack and Discord communities with RAGTime – a RAG-bot from Vectara.
Vectara’s Boomerang stands out as the optimal choice for production use cases, balancing precision, embedding size, and storage costs effectively.
Today, we’re excited to announce that we’re introducing a brand new REST API for Vectara: API v2.
We are so proud of our Built By Vectara Contestants.
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