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The rapid growth of enterprise data demands innovative management solutions, leading to the introduction of an Agentic AI framework. This framework, developed by Dattatreya Raychowdhuri, transforms organizational interactions with complex data ecosystems through collaborative AI agents. By enhancing real-time decision-making and cross-domain analysis, this approach significantly improves data management efficiency.
The Agentic AI architecture utilizes domain-specific agents that work independently yet collaboratively to provide holistic insights. This model not only optimizes query resolution but also enhances data-driven decision-making, allowing enterprises to process information more effectively. The framework's applications span business intelligence and supply chain management, showcasing its versatility in addressing operational challenges.
• Agentic AI framework enhances real-time decision-making through collaborative AI agents.
• Domain-specific agents optimize data processing and improve query resolution efficiency.
Agentic AI refers to a framework that utilizes specialized AI agents for data management.
These agents focus on specific data subsets, enhancing query precision and context-awareness.
The Collaborator Agent orchestrates the system by managing user queries and synthesizing responses.
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