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Industry leaders have quickly embraced RAG as a way to build more intelligent AI applications. In fact, Gartners 2024 AI report advises organizations that want to use generativeAI on private data to prioritize RAG investments. This way, the AI can answer questions using your knowledge base (FAQs, manuals, databases, etc.)
The generativeAI revolution has driven explosive growth in Large Language Model (LLM) applications. To build these AI-powered apps (chatbots, automated agents, RAG systems, etc.) Powerful Agent Framework : Ideal for building autonomous agents and tool-using AI assistants.
Tech giants (Googles Gemini, Metas LLaMA) and startups worldwide are launching generativeAI models. DeepSeek (Chinas entrant) emphasizes cost-effectiveness and Chinese language support. Real-world SaaS use : Developers use LLMs for everything from automated customersupport to personalized content feeds.
From AI Experimentation to Enterprise-Wide Adoption In 2025, executive priorities are shiftingfrom AI experimentation to enterprise-wide adoption. While generativeAI has been widely tested in uncoordinated, department-level pilots, the focus now is on systematic integration to drive efficiency and business impact.
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