AIforDataPipelines

Investigate multi-modal and data pipeline incidents before they become alerts
and get proactive fixes for critical issues.

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Tracer Product Dashboard - Pipeline Monitoring Interface

Say goodbye to false alarms.
True ones investigated before you can look.

Filter out alerts that don't need your attention, and easily find fixes for the ones that do.

A better experience for engineers

Make every alert count

Tracer automatically investigates incidents before they become alerts. Only get alerted when an incident really needs your attention

Resolve incidents fast

Tracer accurately identifies the root cause of pipeline issues and provides relevant fixes for faster time to resolution.

Cut compute costs

Optimize spend across your pipelines' infra, orchestration, and data stacks, all while improving performance.

Why engineers choose Tracer

Bojk Berghuis

Senior Director, Superfluid DX

30%

faster end-to-end runtime

40%

lower compute cost

"Tracer uncovered that the STAR tool was I/O-bound, not compute-bound, and suggested the right fix. Once we approved it, our pipelines sped up instantly."

THE PRODUCT

Tracer in action

Observability for data pipelines

Tracer acts as a buffer between your pipelines and
your on-call engineers, reduces benign alerts, shortens
investigations, and lowers anxiety even when nothing is broken.Tracer is built specifically for data pipelines. With graphs of your workflows, infrastructure, and telemetry, Tracer builds a complete picture of your pipelines, separating what matters from what doesn’t.

Root cause investigation

Tracer runs ambiently, continuously validating multiple
root-cause hypotheses against real execution, across
code, infra, orchestration, and I/O, so you get answers
grounded in truth, not speculation.Tracer starts investigating issues before your team even opens the alert. Pair debug with the Tracer AI agent for deeper investigation.

Get fixes fast

When action is needed, Tracer provides: Draft GitHub
pull requests, Infrastructure and configuration
changes, kubectl commands and scripts, Clear
explanations tied to execution evidence. Nothing is
applied automatically. Your team stays in control.Tracer provides Draft GitHub pull requests, infrastructure and configuration changes, kubectl commands and scripts so you can make fixes fast.

HOW TRACER WORKS

See everything your pipeline does in
three simple steps

Step 1: Deep pipeline connections

Tracer connects to all parts of your pipeline stack through its proprietary eBPF and Otel connectors, minimising setup time.

Step 2: Multi-layered AI reasoning architecture

Each of Tracer AI layers performs a distinct function: alert digestion, hypothesis generation, deterministic review, and reporting.

Step 3: Observability without the time loss

Users see live reasoning and exploration and are only alerted when there is a conclusive answer.

LATEST INSIGHTS

Explore our latest research
and technical insights

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ByTeam Tracer