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RAG Explained: What Is Retrieval-Augmented Generation?

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Retrieval-Augmented Generation (RAG) is a cutting-edge approach in AI that combines large language models (LLMs) with real-time information retrieval to produce more accurate and context-aware outputs. Industry leaders have quickly embraced RAG as a way to build more intelligent AI applications. and real SaaS examples using RAG.

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Best Applicant Tracking Systems for 2025

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Importantly, ATS platforms have evolved with AI-driven features , diversity and bias reduction tools , and deep analytics to meet todays hiring challenges. From cloud-based SaaS solutions to on-premise enterprise software , businesses worldwide are leveraging ATS technology to build efficient, fair, and scalable hiring pipelines.

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DeepSeek vs Claude vs Mistral: Top GPT Competitors in 2025

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Once-dominant ChatGPT (GPT-4) sparked a global AI race, and by 2025 there are powerful new alternatives. Companies now weigh dozens of LLMs each with its own strengths when choosing AI to enhance products and automate workflows. Tech giants (Googles Gemini, Metas LLaMA) and startups worldwide are launching generative AI models.