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
This playbook shows how to build Pydantic models that enable agents to create Meta ad campaigns programmatically. We'll implement the complete workflow from image upload to live ads, with automatic validation for budgets, content safety, and platform requirements built into every step.
This playbook walks you through building an AI-powered cohort analysis system that automatically discovers which customer segments have the highest retention rates. The LangGraph pipeline dynamically analyzes multiple dimensions and delivers AI-generated insights for targeted retention strategies.
This playbook walks you through building an AI-powered CLV analysis system that reveals which customers drive long-term profitability. The LangGraph pipeline applies statistical models to predict behavior and delivers AI recommendations for optimization.
This playbook walks you through building an AI Flow that dissects ecommerce revenue drivers across a customer base. The LangGraph-based system breaks down top-line metrics into their component parts, identifies root causes, and delivers prioritized recommendations to improve performance
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.
