When AI Understands Your Documents, Processes, and Knowledge
In this workshop, you will explore basic and advanced RAG approaches and gain hands-on experience with different ways of building AI solutions using your own documents and data.
What will you do?
- Learn what RAG is and how it enables AI-powered queries over your own data
- Build a basic RAG solution using a vector database
- Explore the more advanced GraphRAG approach for working with interconnected data
- Test RAG with an existing relational database
What does this mean in practice?
AI Powered by Your Own Documents
Instead of searching through folders, AI can answer questions based on internal policies, contracts, technical manuals, documentation, and other company resources.
Rapid Prototyping of Your Own RAG Solution
You will learn how to quickly build a solution for semantic search and working with your own documents using a vector database.
GraphRAG for More Complex Data
You will explore an approach that considers not only content but also relationships between data, for example in supply chains, organizational structures, or project dependencies.
RAG with Existing Databases
You will learn how semantic search can be added to an existing relational database without having to migrate data to a new system.
Who Is This Workshop For?
The workshop is intended for micro, small, and medium-sized enterprises (MSMEs) and their employees who want to connect artificial intelligence with their own documents, data, and internal knowledge, and develop solutions for more efficient information retrieval and use.
Agenda
8:45–9:00
Participant arrival, registration, and coffee
9:00–12:30
Introduction to RAG and AI queries over your own data
Fundamentals of vector databases and building a RAG solution
12:30–13:00
Break
12:30–15:30
Advanced applications: GraphRAG and RAG with relational databases
Hands-on use cases and discussion
All necessary computer equipment will be provided for the practical sessions.
Trainer
Andrej Duh is an expert in artificial intelligence, Big Data, and software development. He works as a technical lead, architect, developer, co-founder, and lecturer. His technical expertise includes Python, TypeScript, C++, and Java. He has more than 25 years of experience working with international companies.
His training sessions focus on hands-on learning and understanding technology through real-world examples and the development of working solutions.
