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How real-time data enables personalization and engagement
Unified User Context at the Speed of Interaction
Get instant access to comprehensive user attributes that combines real-time behavior with historical data, enabling personalized experiences at the moment of engagement.
Real-Time Response Times
Power dynamic product experiences with an API optimized for low-latency lookups, designed to return comprehensive user context in real time from your first API call.
Unified Data Architecture
Eliminate data silos by combining real-time user behavior with historical warehouse data, computed through streaming and batch engines, ensuring consistent, complete, real-time customer context.
Developer-First Design
Built for engineers with seamless SDK integration, declarative attribute definitions, and Git-backed deployments that align with modern engineering practices and CI/CD workflows.
Low-Latency Profiles API
Access user attributes instantly through a low-latency API designed specifically for product applications and AI agents. The Profile API stores and serves user attributes with consistent real-time response times, enabling real-time personalization without adding latency to your application.
Built-in authentication using JWTs and RSA for warehouse connections
Consistent real-time response times across millions of profiles
Central hub, storing attributes definitions, profiles, and handling authentication
Dual-Engine Computation
Leverage both real-time behavioral data and deep historical analysis via complementary processing engines. The streaming engine processes events as they happen for instant context updates, while the batch engine computes from your entire data warehouse for rich, complex calculations that incorporate historical customer data.
Real-time streaming computation for in-session personalization
Warehouse-computed attributes that leverage the entire data history
Automatically join in-session data with historical customer datasets
Integrated Data Foundation
Built on a reliable data foundation that eliminates the fragmentation and inconsistencies typically faced when creating personalized experiences. The Profiles Store is built on your existing Snowplow customer data infrastructure, ensuring high-quality, well-governed data while reducing the maintenance burden on your engineering team.
Same data in-stream as in-warehouse for consistent ML execution
Automatically deduplicate events with data quality validation
Purpose-built flexible infrastructure with transparency and control
