Mario Pilija
MovementNow, Founder
MovementNow, Founder
Zagreb, Croatia
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Experienced IT leader with 16+ years in software architecture, AI engineering, and digitalization. Proven experience in delivering complex, scalable solutions across global industries.
Responsible for strategic initiatives, execution of high-impact projects, and consulting engagements that help organizations navigate digital transformation. Combines expertise in Azure cloud architecture, AI engineering, DevOps, and enterprise software development with strong business insight.
Focus areas include aligning technology with business objectives, guiding digital transformation, and advising on the adoption of intelligent systems.
Experienced IT leader with 16+ years in software architecture, AI engineering, and digitalization. Proven experience in delivering complex, scalable solutions across global industries.
Responsible for strategic initiatives, execution of high-impact projects, and consulting engagements that help organizations navigate digital transformation. Combines expertise in Azure cloud architecture, AI engineering, DevOps, and enterprise software development with strong business insight.
Focus areas include aligning technology with business objectives, guiding digital transformation, and advising on the adoption of intelligent systems.
Area of Expertise
Topics
Vibe Modeling: How AI and MCP Change Power BI Development en
AI can write your emails — but can it build your semantic model?
In this hands-on deep dive, we'll wire up Model Context Protocol (MCP) servers to turn an AI assistant into a real Power BI development partner: one that reads your model, writes and optimizes DAX, refactors measures, generates documentation, and scaffolds entire semantic models from a prompt.
We start with the architecture — what MCP actually is, how MCP servers expose Power BI and Fabric to an AI agent, and how to connect it all to your development environment without handing over the keys to the kingdom. Then we go hands-on.
Live, we'll build and refactor a semantic model through natural language, generate and tune DAX, automate the repetitive modeling work that normally eats your day, and put guardrails around what the AI is actually allowed to touch.
Combining deep Power BI expertise with real-world AI engineering, this session is about practical, production-minded workflows — not demos that collapse the moment they leave the slide. You'll walk away knowing how to set up MCP for your own Power BI projects, where AI genuinely accelerates development, and — just as importantly — where to keep a human firmly in the loop.
This is a level 300 session. You'll get the most out of it if you're already comfortable with Power BI Desktop, semantic models, and DAX.
Unleashing AI's Full Potential with Azure's AI Search and Vector Databases en
With the increasing popularity of Large Language Models (LLMs) and the adoption of patterns such as RAG (Retrieval-Augmented Generation), vector databases have become an indispensable part of modern architectures. What exactly are vector databases? What options do we have in Azure? How can we utilize Azure AI Search, and what significance do its advanced features hold for us? Let's explore together in this lecture."Join us for an insightful exploration into the integration of vector databases with Azure AI Search. We'll delve into how these technologies are reshaping the AI landscape, offering enhanced capabilities for your AI projects.Key Session Highlights:Vector Databases and LLMs: Understanding their critical role in modern AI architectures.Azure AI Search: Discover its powerful capabilities in enhancing search experiences.Advanced Features: Explore key features like semantic search, vector filters, and hybrid information retrieval.Practical Applications: Learn how to apply these technologies in real-world scenarios.Why Attend: This session is ideal for those eager to keep pace with the evolving field of AI and data technology. Whether you're an AI enthusiast, a seasoned developer, or simply curious about the future of AI, you'll find valuable insights and practical knowledge.Join us for a deep dive into Azure AI Search's latest advancements and learn how to leverage these innovative tools in your AI applications!
.NET 6.0 on Azure Functions en
Sa previewom .NET6 verzije frameworka nam je došla i nova verzija Azure Functions Core Tools-a(V4). Koji su nam noviteti, koje su razlike u podršci modeova rada(Isolated vs. In-Process) te kakva nam je development podrška došla sa Visual Studiem 2022 pokazujemo na demo primjeru Durable Fan-Out/Fan-In arhitekture.
Azure Event Hub + Azure SQL Database = <3 en
In modern cloud solution architectures, we have numerous possibilities how to use different "pieces of puzzle" to put scalibility, performances and cost optimizations in the first plan. One of the indispensable part of modern architectures are "event processing hubs" which gives us possibilities to handle a millions of "events" in a real time. Azure Event Hubs is a fully managed Microsoft cloud solution built for that purpose. Through this session, we'll examine different scenarios of using Azure Event Hub through the prism of building modern scalable enterprise data streaming solution.
You developed your ML model via Azure ML studio - now what? en
Razvili ste svoj ML Model putem Azure Machine Learning Studia i želite isti publishati kako bi bio dostupan za konzumaciju. Koje sve opcije imate built-in(ACI/Kubernetes)? Kada ćete koju upotrijebiti? Što ako želite napraviti publish van ponuđenog seta opcija same platforme(App Services)? Kako možete dodati duh poznatog delevopment stacka na publishani endpoint(Swagger) i detaljni monitoring(Application Insights) za zaokružiti cijeli produkt? Odgovore na sva pitanja demonstriramo na primjeru.
MLOps - Let's automate our machine learning development process hr en
Već nam na uši izlazi pojam DevOps. Na taj "buzzword" smo se navikli i prihvatili ga kao nešto dobro, što nam pomaže u svakodnevnom procesu razvoja naših aplikacija. Znamo automatizirati buildove i releasove istih, kolaborirati unutar timova preko različitih alata i dižemo našu efikasnost i produktivnost iz dana u dan. Gdje su machine learning sustavi u cijeloj toj priči? Kako data scientisti i tradicionalni aplikativci mogu lakše i bolje surađivati u razvoju modernih kompleksnih sustava? MLOps nam daje odgovore na ta pitanja. Pokazati ćemo kako nam taj dio Azure DevOps Server platforme nudi mogućnost automatizacije cijelog development procesa ML modela i integracije sa ostatkom sustava.
MLOps - Let's automate our machine learning development process hr en
Već nam na uši izlazi pojam DevOps. Na taj "buzzword" smo se navikli i prihvatili ga kao nešto dobro, što nam pomaže u svakodnevnom procesu razvoja naših aplikacija. Znamo automatizirati buildove i releasove istih, kolaborirati unutar timova preko različitih alata i dižemo našu efikasnost i produktivnost iz dana u dan. Gdje su machine learning sustavi u cijeloj toj priči? Kako data scientisti i tradicionalni aplikativci mogu lakše i bolje surađivati u razvoju modernih kompleksnih sustava? MLOps nam daje odgovore na ta pitanja. Pokazati ćemo kako nam taj dio Azure DevOps Server platforme nudi mogućnost automatizacije cijelog development procesa ML modela i integracije sa ostatkom sustava.
DevOps architecture for development of complex solutions en
When your company services portfolio implies development of complex enterprise solutions that often includes microservices backend, transactional relational databases, datawarehouse, ETL pipelines, no-sql databases, storages, Office365 resources, web & native mobile applications, PowerBI reporting with low-code flows and predictive analytics on top of that there is a lot to orchestrate to achieve high productive and effective development. Things can get even messier if we're talking about hybrid client environments. Luckily, with todays technology and good DevOps architecture you can setup a scalable DevOps environment that supports todays standards for every piece of that complex enterprise solution. In this session, we'll check how are we dealing with this challenges and how our scalable DevOps infrastructure is the backbone of our development that helps us build software supporting latest industry standards.
Model Context Protocol (MCP) for Azure SQL- How AI Agents Can Create, Maintain & Query Your Database en
Model Context Protocol (MCP) is one of the most important new standards in AI engineering. It defines how AI agents can safely interact with real systems—files, APIs, and databases—using structured tools instead of ad-hoc prompts.
In this session, we dive into how MCP works and demonstrate how it can be used to query, maintain, and even help build Azure SQL databases.
We explore the official MSSQL MCP Server, how it exposes schema, metadata, and controlled SQL execution, and how AI agents like ChatGPT or Azure AI Foundry can use it to:
- inspect tables and structures
- run guarded read/write SQL operations
- help automate schema creation and migrations
- generate or validate T-SQL
- assist with troubleshooting and performance tuning
Through live demos, you’ll see how MCP brings safe, auditable, enterprise-grade AI automation directly into the SQL workflow—without giving an LLM full database access or embedding secrets in prompts.
If you’re working with Azure SQL, Copilot, or want to build AI-powered data tooling, this session gives you a clear picture of how MCP will reshape the future of database operations.
Data Saturday Croatia 2026 Sessionize Event
Data Saturday Croatia 2024 Sessionize Event
DataSaturday Croatia 2022 Sessionize Event
Advanced Technology Days 16 Sessionize Event
Advanced Technology Days 15 Sessionize Event
Global Azure Bootcamp 2019. Developers Edition - Križevci Sessionize Event
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