RAG architecture

AI-Agentic-RAG-Agentic-KrishnaG-CEO

AI Agents vs Agentic AI vs Agentic RAG: Demystifying the Next Frontier for Data Scientists

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Artificial Intelligence has transformed from a theoretical construct into a practical powerhouse driving real-world applications across sectors. At the forefront of this revolution lies a new taxonomy of intelligent systems: AI Agents, Agentic AI, and the emergent concept of Agentic Retrieval-Augmented Generation (Agentic RAG). For data scientists—tasked with building intelligent systems, driving innovation, and ensuring scalable impact—it is crucial to differentiate and understand these evolving paradigms.

LLM-Integrity-KrishnaG-CEO

Secure System Configuration: Fortifying the Foundation of LLM Integrity

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When deploying LLMs in enterprise environments, overlooking secure configuration practices can unintentionally expose sensitive backend logic, security parameters, or operational infrastructure. These misconfigurations—often subtle—can offer attackers or misinformed users unintended access to the LLM’s internal behaviour, leading to serious data leakage and system compromise.

LLM-Sensitive-Info-KrishnaG-CEO

OWASP Top 10 for LLM – LLM02:2025 Sensitive Information Disclosure

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While theoretical risks highlight potential harm, real-world scenarios bring the dangers of LLM02:2025 into sharper focus. Below are three attack vectors illustrating how sensitive information disclosure unfolds in practical settings.