The Data Pipeline Health Agent ensures your data pipelines run reliably and efficiently. It monitors executions, detects failures, and recommends improvements—keeping your data flowing without disruption.
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Where every decision is powered by reliable, self-healing data.
Autonomous scheduling, optimization, and observability in one intelligent loop.
Backed by xLake and orchestrated via ADM, the Pipeline Agent works across your stack—ensuring healthy, efficient, and compliant workflows at scale.
The Data Pipeline Agent is part of a multi-agent system—working alongside other specialized agents to share context, coordinate actions, and resolve issues faster. This agent-to-agent collaboration drives smarter decisions and scalable data governance.
Continuously monitors, detects, and remediates data quality issues, ensuring AI-ready data.
Tracks data flow across systems to uncover dependencies, trace root causes, and power intelligent decisions.
Analyzes datasets to surface distributions, anomalies, and structural insights, strengthening quality and governance.
ADM adds intelligence—auto-detection, root cause diagnosis, and corrective action across systems.
Yes. HILT workflows let you approve, delay, or override automated steps.
Failures, retries, latency spikes, scheduler gaps, resource contention, and more.
Native integrations with Apache Airflow, Prefect, Dagster, and more via connectors.
It detects failures, recommends fixes, and can trigger remediation agents to resolve problems.
Yes. You can configure execution cadence, approve overrides, or let the agent auto-adjust based on usage.
By analyzing resource patterns, failure trends, and execution logs to surface actionable insights.
Absolutely. It scales across clouds and platforms via the xLake orchestration layer.
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