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Agents | Data Quality

Stop firefighting data quality.

The Data Quality Agent detects, diagnoses, and resolves issues before they reach your stakeholders.

Your pipelines break. Your team gets paged.

Data quality incidents don't announce themselves. By the time your team notices, stakeholders are already asking questions.

Every incident is a manual investigation

Lineage and quality live in separate systems

Rules are static. Your data isn't.

NEW

REPORT

Build AI on trustworthy data — download the Gartner® guide

You stay in control.
The agent does the work

Review anomalies
before action

Validate findings before automated remediation runs.

Override false positives

Dismiss or reclassify events and retrain detection logic.

Approve policy enforcement

Apply or pause rules dynamically based on operational context.

Validate RCA recommendations

Confirm or correct root cause suggestions before they're committed.

Prevent Future Failures

Approve adaptive guardrails before they're deployed to production.

Data Quality Agent in Action

Monitor Continuously

Scan batch jobs, pipelines, and tables for quality violations.

Analyze with Lineage

Identify source of drift, duplicates, missing values, and stale records.

Diagnose Root Causes

Connect symptoms to pipeline logic, upstream schema changes, or unexpected inputs.

Remediate Proactively

Auto-reprocess only impacted data, flag unresolved records, and document findings.

HITL:

Validate Anomalies

Prevent Future Failures

Recommend adaptive guardrails and freshness policies based on historical patterns.

HITL:

Approve Remediation

Ask the Data Quality Agent Anything

Information Retrieval

“Show me the current data quality scores for our customer tables.”

Which datasets have the lowest completeness this week?

RCA / Investigation

What’s causing the drop in accuracy for our transaction data?

When did the quality score start declining for the product catalog?

Action / Resolution

“Trigger remediation for tables with low accuracy”

Generate a weekly quality report for executive review

Explore the Agent Network

Your team's Monday morning, transformed.

One VP of Data Engineering. Two very different Mondays.

Before ADM

Paged at 6am — quality dashboard red across 12 tables

30 minutes finding the root cause across three tools

Manually rerunning pipelines, hoping the fix holds

Writing a post-mortem with no confidence it won't recur

Downstream BI reports delayed. Business stakeholders asking why.

With the Data Quality Agent

Agent detected the issue at 4am — root cause identified in 28 seconds

Lineage trace surfaced the upstream schema change automatically

You approved remediation in one click — agent reprocessed impacted records

Adaptive guardrail deployed. Incident logged. Compliance audit-ready.

Reports delivered on time. Stakeholders never knew there was an issue.

NEW

EXECUTIVE GUIDE

Improve forecast, on‑shelf, and margin with reliable data

Multi-Agent Intelligence

The Data Quality 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.

Data Lineage Agent

Tracks data flow across systems to uncover dependencies, trace root causes, and power intelligent decisions.
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Agents | Data Lineage

Data Profiling Agent

Analyzes datasets to surface distributions, anomalies, and structural insights, strengthening quality and governance.

Agents | Data Profiling

Data Pipeline Agent

Monitors pipeline execution in real time to detect failures, optimize performance, and maintain pipeline reliability.
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Agents | Data Pipeline

Enterprise Outcomes, Realized

“ADM’s planning reduced data downtime by 50% and quality incidents by 80%. Our team now focuses on strategy, not reactive cleanup.”

- Data Lead, Fortune 500 Financial Enterprise