AutoGen for Enterprise AI Automation

• Proficiency in Python programming
• Experience with LLMs and prompt engineering
• Familiarity with enterprise automation or workflow tools

Audience

• Enterprise AI teams
• Solution architects
• Innovation strategists

AutoGen for Enterprise AI Automation is a hands-on course focused on implementing scalable, intelligent agent systems to automate complex business operations using the AutoGen framework.

This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level AI professionals who wish to deploy multi-agent architectures across enterprise platforms and processes using the AutoGen framework.

By the end of this training, participants will be able to:

• Design and automate enterprise workflows using AutoGen and LLM agents.
• Integrate AutoGen with LangChain for advanced orchestration and context handling.
• Build RAG pipelines and connect enterprise data for contextual automation.
• Connect agents with enterprise platforms like Slack, Jira, and SharePoint.
• Scale and monitor AutoGen deployments in production environments.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

AutoGen in the Enterprise Context

• Why intelligent agents matter for business operations
• Review of AutoGen’s architecture and extensibility
• Security, traceability, and governance considerations

Enterprise Workflow Automation with AutoGen

• Designing multi-agent workflows for task coordination
• Role-based automation scenarios: request handling, approvals, summaries
• Auto-execution and escalation logic for business continuity

AutoGen with LangChain Integration

• LangChain components and compatibility with AutoGen
• Chaining agents and tools with memory, tools, and logic
• LangChain Expression Language (LCEL) for complex workflows

Retrieval-Augmented Generation (RAG) Pipelines

• Connecting AutoGen agents with enterprise knowledge bases
• Embedding, vector search, and retrieval pipelines
• Private data augmentation with open-source or proprietary models

Integration with Enterprise Tools

• Using APIs to connect Jira, Slack, Outlook, SharePoint, and more
• Triggering workflows via chat interfaces and ticketing systems
• Real-time notifications, logging, and auditing

Deployment, Monitoring, and Scaling

• Packaging AutoGen agents for deployment
• Monitoring agent interactions, usage, and performance
• Scaling agents across departments and geographies

Enterprise Use Case Prototyping Lab

• Group ideation: enterprise scenarios for automation
• Building custom agent workflows with instructor support
• Simulating production environments for validation

Summary and Next Steps