Snowplow vs. Building Your Own Data Pipeline
Your data pipeline made sense when you built it, but agentic AI has added new requirements to the spec that never existed before. Data teams maintaining their own pipelines are now on the hook for all of them.
Agentic AI added four new jobs to your data pipeline spec
Now you must be able to track AI agents across your digital estate, make instrumentation an agentic workflow, deliver data that agents can reason over, and support agentic UX on both sides of the pipeline. Snowplow handles all four, so your engineering time goes towards your product, not your pipeline.
What Snowplow Can Do for You
Define and govern your event data
As your product evolves, so does your tracking. Snowplow Event Studio gives every team visibility into which data sets they own, what each event means, how it is structured, and how it has changed over time. That shared understanding is what keeps your data consistent and trustworthy as more agents and analysts depend on it.
Make tracking design and instrumentation agentic
Manual instrumentation is slow, inconsistent, and dependent on developers getting it right every time. An agentic product workflow looks different: a team asks for tracking on a new feature, an agent designs the plan against your existing schemas, generates the code, and opens the PR. Snowplow is built for this workflow, with a design API, schema registry, and SDK generators that agents can read and act on.
Track AI agents across your digital estate, not just human
Until recently, nearly all the events your pipeline collected were about humans. Now AI agents account for a growing share of interactions across your digital estate, and they behave differently. They don't follow the same patterns, they re-emerge from different locations when blocked, and the signals that identify them shift constantly. Snowplow tracks both agent and human behavior, so your digital user data reflects what's actually happening across your platforms and applications.
Make your customer data readable by agents, not just dashboards
The pipeline no longer ends in a BI tool. It ends in an agent talking to a business user in natural language. For that agent to be right, your data needs more than accurate values. It needs provenance, ownership, semantic meaning, relationships, and change history. Flexible schemas carry all of that metadata by design, so the agents reading your data have the context they need to reason reliably.
Support agentic UX on both sides of the pipeline
When the UX is composed by an agent, you need to know what the user did, what they were shown, and why the agent chose to show it. Without all three, you can't debug, optimize, or improve. On the activation side, the agent needs a compressed, information-dense summary of customer context in real time, not a raw data stream. Snowplow supports both collection and activation in an agent-composed UX, so your pipeline keeps up with how your product is being built.
Trust your data pipeline to deliver
An engineering team maintaining its own pipeline pays for the silent failures long after they ship. Snowplow offers SLAs and dedicated support so your pipeline delivers all your critical customer behavioral data to your chosen destinations in real time.
Data Engineering Lead
Global Retailer
