Snowplow, the leader in customer data infrastructure, has launched Snowplow Signals, a real-time customer intelligence system designed to accelerate the development of AI-powered user experiences. With Signals, applications gain access to deep, trustworthy, real-time customer context — enabling hyper-personalized experiences and helping AI agents overcome the cold start problem.

Previously relied upon by data teams at digital-first companies, Snowplow is now empowering product, engineering, and data science teams to build smarter customer-facing applications — from recommendation engines to AI copilots and adaptive user interfaces.

“By infusing real-time behavioral context into an application’s memory, Signals transforms one-off customer interactions into deeply personalized, proactive experiences that drive measurable lift in customer engagement, conversion, and lifetime value,” said Todd Boes, Chief Product Officer at Snowplow.

The Bridge Between AI and Real-Time Customer Understanding

As organizations race to embed AI into their digital products, many face the same obstacles: identifying users in real-time, understanding behavior contextually, and delivering personalized experiences without delay. Traditional infrastructure forces a trade-off between speed and data quality. Signals eliminates this by offering an extensible platform to compute, retrieve, and act on rich customer data — in-session and historically.

Core Capabilities of Snowplow Signals

  • Profiles Store: Provides low-latency access to current and historical user attributes via:
    • Streaming Engine: Captures in-session behaviors in real-time.
    • Batch Engine: Computes long-term attributes from data in your warehouse or lakehouse (e.g., lifecycle stage, ML scores).
  • Interventions: Enables real-time personalized actions like in-app nudges, dynamic pricing, or proactive AI agent support.
  • Fast-Start Tooling: Offers SDKs (Python and TypeScript), guides, notebooks, code samples, and Solution Accelerators to reduce time-to-value.

Built for Product and Engineering Teams

Snowplow Signals is ideal for teams creating AI-powered products that deliver unique experiences to users via recommendation models, personalization engines, and intelligent agents. Key differentiators include:

  • Real-time personalization: No compromise between latency and data depth.
  • Declarative intelligence: Define user attributes in Git and access them via SDKs.
  • Train once, deploy fast: Train models on historical data and instantly activate them on streaming events.
  • Model-agnostic architecture: Integrate with any LLM or ML model.
  • Full control and transparency: Run Signals in your cloud environment with complete governance and auditability.

“Snowplow Signals gives our product and engineering teams the intelligence infrastructure needed to create adaptive, AI-driven experiences for our users,” said Anup Purewal, Chief Data Officer at DC Thomson. “It allows us to go beyond static features and create a personalized genealogy journey for every individual through our vast archives.”

Enterprise-Grade Infrastructure for AI-Driven Experiences

Built on Snowplow’s industry-leading real-time pipeline and streaming engine, Signals ensures data consistency across stream and warehouse while delivering sub-second response times. The platform supports deployments on AWS, Azure, and GCP, and integrates with Snowflake, Databricks, and BigQuery.

With Snowplow Signals, Snowplow positions itself as foundational infrastructure for real-time, AI-enabled digital transformation, supporting growth across product, engineering, and data science teams.

Availability

Snowplow Signals is currently available to select design partners, with general availability expected in Q3 2025. To request a demo or learn more, visit snowplow.io/signals.

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