Snowplow for AWS SageMaker
AI-Ready Behavioral Data for Machine Learning, Analytics, and Agentic Applications
Introduction
Snowplow provides a customer data infrastructure (CDI) that enables organizations to capture complete, high-fidelity event data across every digital touchpoint. With data enriched, governed, and modeled in real time, teams can unlock analytics, machine learning, and AI-driven use cases directly within their AWS environment.
In combination with Amazon SageMaker Unified Studio, Snowplow delivers the behavioral data foundation required to build an deploy trusted, AI-powered solutions. Together, Snowplow and SageMaker enable teams to:
- Run advanced analytics with Amazon QuickSight
- Train and serve ML models (e.g., recommendations, next-best action) with XGBoost and other SageMaker frameworks
- Power real-time, agentic applications (e.g., shopper or support agents) with AgentCore
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Why Snowplow + AWS Sage Maker
Complete, AI-Ready Behavioral Data
Snowplow captures granular clickstream data across web, mobile, server, and emerging digital touchpoints, enriched with 130+ out-of-the-box properties. Unlike black-box tools, data is delivered directly into your AWS environment — structured, contextualized, and machine-learning ready.
Seamless Integration with SageMaker
Data collected and validated by Snowplow feeds natively into SageMaker pipelines for training, inference, and deployment. Whether you’re building recommendation systems, predictive churn models, or AI copilots, Snowplow ensures your ML workflows start with clean, trusted data.
Real-Time Intelligence at Scale
Snowplow’s event stream powers low-latency use cases in SageMaker — from triggering dynamic recommendations to supplying up-to-the-second context for agentic applications. Organizations can optimize performance and reduce operational overhead with governance built in at every stage.
Example Use Cases
Customer 360 & Personalization
Stream user actions into SageMaker to predict next-best offers and drive personalization at scale.
Real-Time Analytics
Deliver accurate behavioral data to QuickSight for business teams while simultaneeously powering ML pipelines.
Agentic Applications
Provide low latency user context to support intelligence shopper or support agents in real time.
Accelerate Your Data Journey
Real-Time Shopper Features using Apache Flink
Real-time feature engineering with Snowplow and Apache Flink, for live personalization of an ecommerce store.
Real-time gamer trophies with Flink
Analyze player behavior, game context and play progression in real-time to unlock achievements for a AAA live-service game. Coming soon - Reach out to us for release information.