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Generative AI
Apr 7, 2025
A benchmark for verifying chain-of-thought
A Chain-of-Thought is only as strong as its weakest link; a recent study from Google Research created a benchmark for Verifiers of Reasoning Chains
Cobus Greyling
Cobus Greyling
Generative AI
Apr 2, 2025
Seven RAG engineering failure points
Explore the seven key failure points in engineering RAG systems, from missing content and retrieval errors to wrong formats and incomplete responses.
Cobus Greyling
Cobus Greyling
Generative AI
Mar 31, 2025
UniMS-RAG: Unified multi-source RAG for personalised dialogue
Explore UniMS-RAG, a unified framework that enhances LLMs by integrating multi-source retrieval and self-refinement for highly personalized AI dialogues.
Cobus Greyling
Cobus Greyling
Enterprise search
Mar 30, 2025
How is RAG reinventing enterprise search and reducing time-to-insight?
RAG transforms enterprise search from keyword matching to context-aware intelligence. Learn how retrieval-augmented generation cuts time-to-insight, reduces hallucinations, and powers faster decisions.
Juhi Tiwari
Juhi Tiwari
Generative AI
Mar 29, 2025
Breaking knowledge silos with RAG: The future of enterprise search
Fragmented knowledge kills productivity. Discover how retrieval-augmented generation (RAG) breaks down enterprise data silos and delivers context-aware answers, at scale, on the Kore.ai Agent Platform.
Juhi Tiwari
Juhi Tiwari
Generative AI
Mar 28, 2025
What is RAG - Retrieval-Augmented Generation ?
Retrieval-augmented generation (RAG) improves LLM accuracy by grounding responses in real enterprise data. Learn how RAG works, when to use it, and how Kore.ai uses it to power secure, context-aware AI agents.
Juhi Tiwari
Juhi Tiwari
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