The world has spent the last year experimenting with Large Language Models. We’ve seen the demos, we’ve played with the chatbots, and we’ve felt the potential. But as 2026 unfolds, the conversation in the tech community is shifting. The question is no longer “What can AI do?” but rather “How do we deploy, scale, and secure it in production?”
Moving a Generative AI application from a “cool prototype” to a reliable enterprise tool is a significant engineering challenge. It requires a new framework—GenAIOps.
The Challenge of Production-Ready AI
Building for production means moving past simple prompt engineering. It requires solving for:
- Experimentation & Evaluation: How do you track versions of prompts and models to ensure performance doesn’t degrade?
- RAG Architectures: How do you securely connect LLMs to your private business data to provide accurate, real-time answers?
- Monitoring & Safety: How do you implement logging to catch evaluation-serving skew and ensure your AI remains within its safety guardrails?
Hands-on in Riga: April 1st, 2026
To address these challenges, Europe Cloud—a Premier Google Cloud Partner—is bringing a deep-dive technical workshop to Latvia: “Generative AI in Production.” Hosted at StartUp House Riga, this isn’t a seminar for spectators. It is an intensive, one-day training led by Nikita Matatov, Authorized Google Cloud Trainer and Data Engineer at Europe Cloud.
The Engineering Roadmap
The workshop is structured around four high-intensity modules designed for data engineers, DevOps specialists, and software architects:
- Introduction to GenAIOps: Understanding the shift from traditional MLOps to the specific requirements of LLM systems.
- Managing Experimentation: Working with RAG and ReACT architectures and implementing frameworks for model evaluation.
- Lab: Unit Testing Generative AI Applications.
- Productionizing GenAI: Focusing on deployment, packaging, and versioning while ensuring prompt security.
- Lab: Vertex AI Pipelines & Safeguarding with Gemini API.
- Logging and Monitoring: Utilizing Cloud Logging and continuous validation to ensure prompts generalize effectively over time.
Build, Test, Deploy
The day concludes with a practical focus: the Gemini Evaluations Playbook. Attendees will leave not just with a theoretical understanding, but with the practical experience of having built and safeguarded a functioning AI system on Google Cloud.
Join the Riga Tech Community
We believe that the best way to learn is to build together. This workshop is free to attend and offers a unique opportunity to network with the local AI and Data Engineering community at StartUp House.
Event Details:
- When: March 24, 2026 | 09:00 – 16:30
- Where: StartUp House Riga (Roberta Hirša iela 1)
- Requirement: Mandatory laptop for hands-on labs.
Secure your spot and lead the next wave of AI implementation.
