Connecting Anomalo’s Autonomous Data Insights with ServiceNow’s Workflow Data Fabric

Today, despite having more sophisticated monitoring, advanced catalogs, and complex pipelines, manual investigation and root cause determination continue to be the norm. Too much time is still spent by data owners, stewards, and engineers investigating what changed, why a pipeline broke, and context-switching into data tooling just to determine what that failure really means for the business.

We are excited and proud to announce our partnership and integration with ServiceNow’s Workflow Data Fabric (WDF)—a unified data connectivity and governance layer. Through this partnership, Anomalo’s agentic data quality platform and autonomous insights connect directly with ServiceNow Data Catalog within WDF for proactive governance that enables faster enterprise AI and decision-making.

Anomalo’s Agentic Platform: A System That Doesn’t Wait to Be Asked

Anomalo’s Self-Driving Data is a new category of agentic capabilities where data effectively self-monitors. Unlike traditional data quality checks or observability tools, Anomalo’s agents:

• Continuously Monitor: Watching the enterprise data for quality indications, and surfacing meaningful changes and events of note.
• Autonomously Investigate: When a significant event occurs, the system doesn’t just alert you. It auto-discovers what changed, why it happened, and where the impact ripples to in the downstream systems.
• Take Action: Assesses criticality and automatically follows runbooks, integrating with ServiceNow to remediate and resolve issues quickly.

“The companies that will win in the age of AI are the ones that understand their data best, at a speed only autonomous systems can sustain. Self-Driving Data is not about replacing your team, it’s about ending the parts of their job that should have been automated a long time ago, so they can focus on the parts that can’t be.” — Elliot Shmukler, Anomalo CEO

ServiceNow WDF: The Context Layer for Enterprise AI

ServiceNow’s Workflow Data Fabric (WDF) provides an AI-ready foundation, unifying structured, unstructured, and streaming data context into a single trusted source of truth for AI agents and workflows to act on. Within WDF is ServiceNow Data Catalog—the layer where metadata, data quality signals, and observability findings converge into business-relevant context.

WDF maintains high-value inputs in the form of data quality signals, observability findings, business-relevant performance, and context insights. These signals create a virtuous loop as WDF grows smarter. The smarter WDF gets, the deeper organizations can integrate and trust agentic workflows and downstream business decisions.

The Integration: Anomalo Context, Directly in WDF’s Data Catalog

Anomalo pushes rich data quality and observability context into ServiceNow Data Catalog, augmenting it with historical and longitudinal data quality metrics, metadata changes, and performance insights.

What this means for your data team:

• Unified Visibility: Anomalo health statuses and detected issues seamlessly appear directly in the ServiceNow Data Catalog for the usage datasets they tool upon.
• Rapid Troubleshooting: When something breaks, your team shouldn’t have to guess or jump between tools to understand it. With this integration, users in ServiceNow Data Catalog can instantly answer why it broke, where it broke, and what it affects — all in one place. The result: faster root cause analysis you can actually explain, and impact assessments you can actually trust.
• Prescriptive Insights: Downstream workflows and agents get valuable context from WDF to granularly know the quality and applicability of the data they are consuming.

What’s Next?

This is just the first peek. Together, we are committed to deepening the integration to bring enhanced monitoring, investigation, and prescriptive insights into WDF workflows for an improved overall experience.

Ready to see how an autonomous data system can transform your ServiceNow environment? Reach out to your Anomalo representative today to learn more and get started.

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