Agentic AI in Enterprise

Agentic AI in Enterprise: Harnessing Agentic AI for Business Transformation

Architect your autonomous logic and master the high-performance protocols of modern enterprise intelligence. Agentic AI in Enterprise provides a definitive, engineering-first roadmap to the most significant shift in business automation since the digital revolution. Learn how to move beyond static bots to high-velocity, goal-oriented discovery—bridging the gap between a standalone script and a sophisticated, agentic-integrated ecosystem—ensuring your technical projects are resilient, scalable, and ready for the 2026 global technology landscape.

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What You Will Learn:

Foundations of Agentic Architecture: Master the core principles of intelligent agents that utilize contextual reasoning and memory retention to enhance enterprise operations.

Modern LLM Optimization Workflows: Step-by-step guidance on utilizing Retrieval-Augmented Generation (RAG) and fine-tuning to maintain peak operational integrity in your AI agents.

Scalable Deployment Patterns: Discover how to utilize cloud, hybrid, and on-premises models and integrate vector databases to maintain the structural integrity and technical agility of your AI workflows.

Strategic Security & Governance Integrity: Learn advanced techniques for maintaining information security through robust governance frameworks and ethical AI adoption—ensuring the technical agility of your evidence-based AI delivery.

Who This Book is For: This professional-grade guide is essential for AI Architects, Data Scientists, and Enterprise Leaders. It is an invaluable resource for any technical lead—including those building highly advanced, autonomous graduation projects like Smart Guard—aiming to master the structural integrity and technical agility required for modern, evidence-based software and agentic system delivery.

Product Details:

Format: Digital PDF / EPUB Download

Authors: Sumit Ranjan; Divya Chembachere; Lanwin Lobo

Publisher: Apress (Springer Nature)

Published: August 13, 2025

Pages: 406

ISBN-13: 9798868815423 (Electronic) / 9798868815416 (Paperback)