An Azure-based agentic AI architecture using Snowplow creates sophisticated, autonomous systems that understand and respond to customer behavior.

Data foundation:

• Snowplow serves as the comprehensive behavioral data source, capturing every customer interaction across all touchpoints with rich context and metadata
• Stream Snowplow events through Azure Event Hubs to Azure Databricks or Stream Analytics for immediate processing and feature computation

AI agent capabilities:

• Use Azure Cognitive Services, custom ML models, or integrated LLMs to process behavioral patterns and make autonomous decisions about customer interactions
• Deploy AI agents that can autonomously:
  
  • Adjust pricing based on behavior patterns
  • Recommend products using real-time context
  • Modify UX elements for personalization
  • Trigger support interventions proactively

Continuous learning and optimization:

• Create feedback loops where Snowplow captures the results of agentic decisions
• Enable the AI to learn and improve its autonomous responses over time
• Leverage Snowplow Signals to provide AI agents with real-time customer attributes and enable immediate interventions

This creates truly responsive agentic experiences that adapt to customer behavior in real-time, making autonomous decisions that improve customer satisfaction and business outcomes.