Event-Driven AI Agent Workflows for Document Automation

Manual document processing and form filling are slow, error-prone tasks that can be revolutionized with modern AI. By combining event-driven architecture with intelligent agents, you can build systems that automatically ingest, analyze, and act on complex documents. In this course, you will learn how to design and implement event-driven agentic workflows that process documents and fill forms with high accuracy. You will explore how to integrate Retrieval-Augmented Generation (RAG) and establish human-in-the-loop feedback mechanisms to ensure quality control. What you'll learn: - Understand the core concepts of event-driven architecture and AI agents - Apply Retrieval-Augmented Generation (RAG) to extract precise information from unstructured text - Design human-in-the-loop validation steps to review and correct agent decisions - Configure event triggers to automate document ingestion and form-filling tasks - Use vector databases and modern prompt engineering to optimize agent performance - Implement error handling and state management within agentic pipelines The course begins with foundational definitions of event-driven systems and AI agents, ensuring you understand the core architecture before moving to practical implementation. You will then progress through written explanations and code examples that show you how to connect document parsers, vector stores, and validation interfaces. This text-based course is designed for software developers, data enthusiasts, and automation engineers who want to learn agentic workflows from the ground up. No prior experience with AI agents is required, though a basic understanding of programming concepts is helpful. Start reading today to build smarter, event-driven automation pipelines.