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.

Unified
Realtime

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

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

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.

Production-Grade Performance

Access user attributes in milliseconds through an ultra low-latency API designed specifically for product applications and AI agents. The Profiles API stores and serves user attributes with consistent real-time response times, enabling real-time personalization without adding latency to your application.

tick

45ms p50 response times from the Profiles API enable true in-session personalization

tick

Consistent real-time response times across millions of profiles

tick

Central hub, storing attributes definitions, profiles, and handling authentication

Low-Latency

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.

tick

Real-time streaming computation for in-session personalization via Interventions

tick

Warehouse-computed attributes that leverage the entire data history

tick

Automatically join in-session data with historical customer datasets

Engine Computation

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.

tick

Same data in-stream as in-warehouse for consistent ML execution

tick

Automatically deduplicate events with data quality validation

tick

Purpose-built flexible infrastructure with transparency and control

Diagram showing data flow from an Application using Signals SDK sending events to Snowplow Platform in a Cloud Account with a Pipeline processing events to a Data warehouse, and the Signals component pushing interventions and getting user attributes back to the Signals SDK in the Application.

Get Started

Building AI-powered applications? Spin it up. Inspect the architecture. Watch your first intervention fire — all in under 10 minutes. Snowplow helps eliminate engineering complexity so you can focus on delivering smarter customer experiences.