Agentic AI

In this step-by-step tutorial, learn how to build and deploy a Contract Research agent for legal document automation with IBM watsonx Orchestrate, Box MCP, and AI tools.

Learn how to build an event-driven agentic AI system using Confluent Cloud and watsonx Orchestrate. Learn how to consume events from a Kafka topic using a watsonx Orchestrate agent, and configure the agent to analyze incoming events as they arrive. To add business context, the agent also references a set of documents, such as policies, procedures, or reference material, and correlates them with event data when generating insights.

Learn how Model Context Protocol enables scalable multi agent AI systems through client, server, and hybrid architecture patterns, LLM placement strategies, reusable AI agents, dynamic orchestration, enterprise design trade offs, and real world implementation guidance.

Build a simple intelligent virtual agent (IVA) system powered by IBM Watson Speech and Genesys Bot by integrating voice and channels for an IBM watsonx Orchestrate agent.

Learn how to use external LLMs with watsonx Orchestrate AI Gateway, which allows for more flexibility and choice in building AI-powered agents.

Build an AI-powered customer care assistant using IBM Sterling OMS, n8n, and Large Language Models to automate order tracking, enable real-time order status, improve omnichannel customer support, and modernize enterprise order management with agentic AI workflows and OMS APIs.

Learn how to use IBM Bob to automate the full process of building and deploying watsonx Orchestrate agents and MCP tools.

Deploy crewAI microservice on IBM Code Engine and integrate with watsonx Orchestrate for custom AI logic, multi-agent workflows, and automation.

Learn how to create MCP tools on watsonx Orchestrate and build agents that consume these MCP tools.

ContextForge MCP Gateway is an open-source technology for managing and securing MCP servers for AI agents.