Ready to move beyond basic AI experiments? Let's dive into building reliable automation systems with modern LLMs.
We'll cover:
-OpenAI vs Anthropic: API comparison and selection criteria
-Prompt engineering patterns that work in production
-Scalable architecture for AI automation systems
-Practical RAG implementation strategies
-Real-world deployment and cost optimization.

Expect concrete examples, architecture insights, and battle-tested practices for building AI automation tools that actually work in production.For engineers and technical leads who want to move from proof-of-concept to production-ready AI systems. 

I'm excited to share our journey of transforming technical support at Teltonika through AI automation. We faced a challenging question: how do you build an AI assistant that not only understands complex technical queries but actually helps solve real problems? I'll take you behind the scenes of our AI assistant's architecture, from its initial conception to full implementation. You'll see how we tackled the challenges of integrating AI with our existing systems, trained it to understand technical context, and most importantly, made it truly useful for both our support team and customers.

Security and privacy concerns holding back your AI implementation? Let's change that. Drawing from our hands-on experience at Gurtam, I'll share practical strategies for deploying LLMs in security-sensitive environments. We'll explore how to expand AI capabilities beyond basic interactions while keeping your data protected. Join me to discover how to make AI both powerful and secure in your enterprise environment.