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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Agentic AI meets real-time data: Vectara and Confluent unite streaming intelligence with always-on governance to deliver trustworthy, event-driven AI agents that act safely and stay grounded in the freshest version of truth
A costly lesson in why AI outputs must be verifiable
Most agents today are tool loops, but making them production-grade is the real challenge. Vectara’s Agent Framework takes care of orchestration, scaling, and reliability so teams can focus on building features that matter.
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.
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