Tag: enterprise AI
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Governance is the missing layer in AI Agent design
The autonomy paradox Autonomous AI agents are no longer a speculative future, they’re already at work. From customer service bots that schedule appointments to internal copilots that automate documentation or code review, these systems are increasingly capable of making decisions and taking actions without any human intervention. This rise in autonomy brings clear benefits: speed,…
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From Standard RAG to Agentic RAG
How Retrieval-Augmented Generation is evolving into Self-RAG and Agentic RAG Systems Retrieval-Augmented Generation (RAG) has become one of the most widely used techniques in enterprise AI systems. It combines large language models with external knowledge sources, enabling more grounded and context-aware outputs. For many applications, especially those involving static documents or FAQs, RAG offers a…
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Agentic AI governance is now a business imperative
Enterprise AI has moved past assistants that wait for instructions. We are now dealing with systems that can pursue objectives independently, make decisions in real time, and act without being told. These are not chatbots or copilots. These are autonomous agents with the capacity to plan, adapt, and take initiative based on defined goals. In…