Neeraj Choudhary
Neeraj is a Senior Operations Specialist at Google, focused on driving comprehensive process improvements and building intelligent, proactive solutions for complex operational challenges. Combining expertise in data analytics and machine learning with a passion for AI to eliminate workflow inefficiencies and design scalable, optimized operations.
He holds an MSc in Data Analytics and has a strong background in international research. Neeraj contributed to the NEWTON Project, a large-scale, European-funded (Horizon 2020) initiative. Additionally, he has published two peer-reviewed data science research papers at international conferences (IICE-2019 and Edulearn-2019).
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In large-scale distributed enterprises, traditional Knowledge Management (KM) systems face a critical failure mode: static documentation cannot keep pace with evolving operational realities and regional nuances. This "knowledge latency" forces employees out of self-service workflows and into costly support ticketing queues. This paper introduces SENTINEL, a geo-contextual AI framework designed to shift enterprise support from reactive retrieval to proactive interception. The architecture employs a novel dual-engine system integrated into an omni-present interface. The first engine utilizes Large Language Models (LLMs) to conduct pre-emptive, historical case-grounded audits of documentation, generating a "Contextual Density" score that identifies friction zones. The second engine is an autonomous Retrieval-Augmented Generation (RAG) agent that surfaces in-situ via a location-intelligent assistant window, resolving queries in real-time. By functioning as a strategic "defensive barrier" at the point of origin, SENTINEL demonstrates how a proactive AI assistant can drive high-fidelity, in-situ case deflection.
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