AI Engineer & Architect. I designed the personalization architecture for the world's largest jewelry company and automated claims handling for the leading insurance company in the Nordics
What if you could compress months of data analysis into minutes, with better results? Let's explore how agents can transform data into a value-generation engine, delivering prioritized business recommendations and immediate ROI.
In this playbook, we'll build a funnel optimization agent that analyzes GA4 ecommerce data with BigQuery SQL, generates recommendations for both product strategy and funnel improvements, and creates an executive summary with prioritized action items to boost conversion rates and increase revenue.
In this playbook, we'll build a customer acquisition reporting agent that analyzes GA4 traffic patterns through BigQuery SQL, generates channel-specific AI recommendations, and provides actionable insights to improve marketing effectiveness.
In this playbook, we'll build a GA4 Analytics Agent that queries cost-effective BigQuery aggregations of Google Analytics data and uses AI to translate natural language into precise SQL, giving your team direct access to insights.
This playbook walks you through building a cost-aware SQL agent that delivers actionable insights from BigQuery. The agent helps data teams democratize access to analytics and avoid unexpected costs through validation and a built-in protection mechanism.
Building agents in Python has just become faster and more reliable. In this tutorial, you will learn how to build robust, type-safe AI agents in minutes with Pydantic AI.
