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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HHEM-2.1-Open is the de facto open-source hallucination evaluation model for RAG, but how much better is the commercial version available in Vectara’s platform?
In financial services, analysts spend countless hours piecing together insights from internal and external documents and research to craft investment memos. What once took weeks of manual effort can now be compressed into hours with Vectara Enterprise Deep Research
A Comprehensive guide to MCP and the new enterprise interoperability paradigm that is powering the future of agentic workflows.
How Enterprise Deep Research can advance discovery of internal company documents to create onboarding guides for new employees.
The new Vectara Admin Center provides a centralized, intuitive interface for on-premise and VPC customers to manage their Vectara deployments. It empowers DevOps and IT Admin teams with centralized visibility and control to prevent RAG Sprawl overhead.
How Enterprise Deep Research can shorten RFP processing time from weeks or days to hours or even minutes.
Deep Research for the Enterprise is poised to become the killer app of generative AI, unlocking a powerful way to explore nuanced, data-rich questions for decision making by tapping directly into their own document repositories.
Context Engineering is emerging as the evolution of prompt engineering. Yet larger context windows can backfire: too many tokens invite noise, contradictions, and diminishing returns.
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