What Is Agentic AI?

Agentic AI solves complicated, multi-step issues on its own by using advanced reasoning and iterative planning

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AI agents collect and analyze data from a variety of sources, including digital interfaces, databases, and sensors

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Retrieval-augmented generation (RAG) is one approach used in this stage to access private data sources and provide precise, relevant results

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Application programming interfaces let agentic AI quickly execute its intentions by integrating with external tools and software

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By feeding agentic AI data from its interactions to build models, a feedback loop, or “data flywheel,” helps it grow

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With solutions developed using NIM Agent Blueprints, NVIDIA partners, like as Accenture, are assisting businesses in utilizing agentic AI

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