Agentic Ai Serverless Ai Integration
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Agentic AI & Serverless AI Integration
Author: Larry Shawn
language: en
Publisher: Independently Published
Release Date: 2025-03-22
Book Title: Agentic AI & Serverless AI Integration: N8N Automation Tool for Orchestrating Autonomous AI Workflows with LangChain, AutoGen, LangGraph, and Serverless Execution Amazon-Optimized Book Description: Unlock the next evolution of AI development with Agentic AI & Serverless AI Integration-the essential, hands-on guide for building real-time, autonomous AI systems that scale. This book is your comprehensive blueprint for designing, deploying, and managing intelligent multi-agent systems using powerful tools like LangChain, AutoGen, and LangGraph, seamlessly integrated into serverless AWS environments and n8n's no-code orchestration platform. Whether you're an AI engineer, cloud architect, or automation professional, you'll learn how to harness the full potential of Python, Hugging Face Transformers, and LLM-driven agents to streamline business operations, optimize workflows, and drive intelligent automation at scale. Explore how to implement LangChain-powered AI agents with persistent memory, dynamic reasoning, and modular pipelines. Master AutoGen's multi-agent collaboration framework for task delegation, human-agent interaction, and contextual adaptability. Deploy serverless microservices that power real-time decision-making-efficient, secure, and compliant with modern enterprise standards. Inside this book, you'll gain actionable insights into: Architecting cost-effective, serverless AI systems with AWS Lambda, EventBridge, and Step Functions Building modular agentic frameworks with LangChain, LangGraph, and PyTorch 2.0 Integrating AutoGen to coordinate intelligent agents across complex workflows Orchestrating end-to-end automation with n8n's low-code/no-code platform Enabling secure, scalable, and compliant AI operations for enterprise-grade applications Deploying LLMs as operating systems for data processing, API calling, and human-like reasoning Creating real-world workflows for sales automation, customer support, analytics, and more With extensive code walkthroughs, architecture diagrams, and real-world use cases, this book empowers you to bridge the gap between state-of-the-art AI and practical, production-ready deployment. If you're ready to build the next generation of autonomous, intelligent, and serverless systems, this book will show you how-step by step. Perfect for: Machine learning engineers, AI developers, DevOps teams, solution architects, automation engineers, and technical product managers working with LLMs, serverless infrastructure, and AI-driven automation. Build smarter. Scale faster. Automate everything.
Data-Driven Agentic AI: Integrating Data Science and Machine Learning
Data-Driven Agentic AI explores the emerging paradigm where autonomous agents interact with data, tools, and humans to solve complex problems across industries. Bridging the gap between data science, machine learning, and intelligent systems design, this book offers a detailed blueprint for building agentic AI that is autonomous, adaptive, and trustworthy. The book begins by grounding readers in the foundations of agency in artificial intelligence — defining key traits such as autonomy, goal orientation, and memory. It then builds into the architectural and technical elements required to create scalable and reliable agents, covering vector-based memory, tool integration, prompt orchestration, and multi-modal data pipelines. Key implementation frameworks like LangChain, AutoGen, and CrewAI are examined alongside infrastructure strategies for deploying agents in real-time, cloud-native environments. Extensive focus is placed on evaluation methodologies, debugging techniques, security, and compliance — equipping readers to monitor, align, and govern autonomous agents responsibly. Use cases span finance, healthcare, customer service, and robotics, demonstrating how agentic AI transforms industry practices. The final chapters explore collaborative human-agent interaction, ethical design, emergent behaviors, and decentralized multi-agent systems. A hands-on guide for practitioners concludes the book, detailing tools, workflows, and adoption roadmaps. Whether you're a data scientist, ML engineer, product leader, or researcher, this comprehensive guide delivers the theoretical grounding and practical insights to design and deploy intelligent, data-driven agents for the real world.
Serverless Agentic AI
Author: Ronald Taylor
language: en
Publisher: Independently Published
Release Date: 2025-02-27
Serverless Agentic AI: Build Autonomous AI Agents Using Serverless Technology for Scalable Automation and Seamless Cloud Integration Unlock the future of AI automation with Serverless Agentic AI, the definitive guide to building intelligent, self-directed AI agents using serverless computing. Whether you're an AI engineer, cloud architect, or technology leader, this book provides the knowledge and tools to design scalable, efficient, and cost-effective AI systems that operate autonomously-without the burden of managing infrastructure. Grounded in cutting-edge research and real-world applications, this book takes you step by step through designing agentic AI systems that leverage retrieval-augmented generation (RAG), multimodal intelligence, and multi-agent collaboration. You'll explore AWS-native solutions, cloud-edge hybrid approaches, and cognitive frameworks to develop AI-driven applications that adapt dynamically to their environments. From AI-powered business automation to real-time decision-making, this book demonstrates how to integrate serverless functions, event-driven architectures, and scalable storage solutions to build highly responsive, context-aware AI agents. Through hands-on insights and practical strategies, you'll master techniques for optimizing performance, securing AI workloads, and ensuring compliance-while keeping operational costs under control. What You'll Learn: Architect autonomous AI agents using serverless computing and modern cloud technologies. Implement retrieval-augmented generation (RAG) to enhance agent decision-making with real-time knowledge. Design multi-agent AI systems that collaborate, learn, and execute complex workflows. Optimize AI execution time, resource allocation, and cost-efficiency in large-scale automation. Deploy context-aware multimodal AI applications that integrate text, vision, and audio intelligence. Secure AI workloads using identity and access management (IAM), encryption, and compliance best practices. Leverage edge computing for low-latency AI inference and hybrid cloud strategies for maximum scalability. With insights from modern AI architectures, AWS-native tools, and practical agentic AI frameworks, Serverless Agentic AI bridges the gap between theory and hands-on implementation. Whether you're building next-generation chatbots, predictive analytics platforms, or fully autonomous AI-driven enterprises, this book equips you with everything you need to design intelligent, self-directed AI systems that operate at scale. Stay ahead of the AI revolution-build, deploy, and master Serverless Agentic AI today.