Retrieval-Augmented Generation (RAG) has emerged as the industry standard for building AI systems that are both intelligent and secure—capable of delivering accurate, context-aware responses based exclusively on your organization’s private data.
Retrieval-Augmented Generation (RAG) is a powerful architecture for grounding large language models in trusted data—but building a RAG system that works reliably in production requires more than connecting a model to a vector database.
Many teams can build a basic Retrieval-Augmented Generation (RAG) prototype – but far fewer can make it accurate, reliable, and production-ready.
In this focused 90-minute advanced workshop, participants will learn the practical techniques used to transform a simple RAG pipeline into a high-performance AI system suitable for real-world deployment
Powerful AI solutions are no longer limited to data scientists and engineers. In this fast-paced 90-minute executive workshop, you will learn how to design and deploy a secure, enterprise-ready private AI assistant—without writing code.
Artificial intelligence is rapidly evolving beyond chatbots and single prompts. A new generation of systems – known as AI Agents – can pursue goals, use tools, maintain memory, and execute multi-step workflows with minimal human intervention.
Microsoft Copilot Studio enables organizations to build custom AI copilots and intelligent agents with low or no code that automate workflows, retrieve knowledge, and interact with users through natural language.
Claude Cowork is an AI “digital coworker” designed to assist with real workplace tasks such as analyzing documents, organizing files, conducting research, and generating reports.
Claude Code is Anthropic’s agentic coding assistant that runs directly in a developer’s terminal and works with the local codebase. It can analyze projects, edit files, run commands, and automate development tasks through natural-language instructions.
