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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This blog post focuses on the technical details of our latest iteration of Multilingual Reranker v1 which enables state-of-the-art retrieval performance across 100+ languages. Our latest model provides qualitative performance on par with industry leaders like Cohere and surpassing the best open source models. Our latest model also provides users with blazing-fast inference at minimal cost, with the additional capability of rejecting irrelevant text based on score-based cut-offs.
Today, we’re proud to announce 2 significant enhancements to our generative response capabilities. These new features are aimed at significantly improving the developer experience as well as giving Vectara administrators better ability to review and analyze conversations their users have had with the system.
When running Gen AI applications, it is important to decide whether to build or buy the RAG infrastructure on which to run your application. This article helps you to make that decision.
Leveraging Vectara’s API to build Sankofa, a browser extension that allows anyone to chat with their web content history
Discover how Stream Query reduces latency by delivering Gen AI responses in real-time chunks, eliminating the frustration of waiting for LLM’s response
How to measure the quality of your Vectara RAG pipeline with RAGAs
Vectara’s Factual Consistency Score (FCS) offers an innovative and reliable solution for detecting hallucinations in RAG. It’s a calibrated score that helps developers evaluate hallucinations automatically. This tool can be used by our customers to measure and improve response quality. The FCS can also be used as a visual cue of response quality shown to the end-users of RAG applications
Discover Vectara’s Four Principles for UI Development in the Age of AI.
Utilize Create-UI for a comprehensive, full-screen chat application integrated with Vectara’s chat capabilities. For more compact solutions, embed React-Chatbot within your React application, offering users a sleek, minimally intrusive chatbot widget.
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