CluedIn has once again been recognized in the 2026 Gartner® Magic Quadrant™ for Augmented Data Quality Solutions (ADQS).
The ADQS market evaluates vendors that apply AI, machine learning, and automation to enhance data profiling, validation, matching, monitoring, and remediation, enabling organisations to deliver trusted, AI-ready data.
We believe this continued recognition reflects both the maturity of our augmented data quality capabilities and our focused approach to modern enterprise data management.
Understanding the ADQS Market
Augmented Data Quality Solutions use automation and AI to improve traditional data quality processes.
These platforms typically support:
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Data profiling and continuous monitoring
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AI-assisted matching and entity resolution
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Data validation and rule orchestration
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Issue detection and remediation workflows
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Alignment with governance and policy enforcement
As AI initiatives move into production, organisations require data quality that operates continuously, not periodically, within operational workflows.
Focused Depth in Modern Data Quality and MDM
The Magic Quadrant defines Niche Players as vendors that often specialise in particular domains, industries, or use cases, delivering strong value within those focused areas.
CluedIn’s focus has been deliberate.
Rather than building a broad portfolio across every possible data management function, we have concentrated on delivering:
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AI-assisted entity resolution and mastering
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Graph-native data modelling
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Continuous validation and enrichment
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Integrated Master Data Management (MDM)
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Federated governance and policy automation
Our customers typically engage us for enterprise data domains where accuracy, traceability, and AI-readiness are critical, including customer, product, supplier, and asset data.
This focus allows us to move faster in areas such as AI-driven matching, knowledge graph modelling, and automation-led data quality improvement.
From Augmented to Agentic Data Management
While augmented data quality enhances human-led workflows, we see the market evolving further.
As Tim Ward, CEO of CluedIn, explains:
In this model:
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AI agents analyse and map new data sources
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Matching and mastering continuously improve
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Policies and governance evolve dynamically
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Business knowledge is embedded directly into the data management engine
This represents a shift from static rule maintenance toward continuous, agentic data operations.
What This Means for Enterprise Data Leaders
Recognition in the 2026 Magic Quadrant for Augmented Data Quality Solutions reinforces several industry realities:
AI-ready data is foundational.
AI and analytics initiatives depend on trusted, mastered, and governed data.
Data Quality and MDM are converging.
Matching, mastering, validation, and governance must operate as an integrated system.
Specialisation drives depth.
Focused platforms can deliver strong value for specific enterprise data domains and AI-driven use cases.
Organisations evaluating data quality solutions should assess not only breadth of features, but alignment with their strategic data priorities and complexity profile.
Looking Ahead
We are proud of this continued recognition in the Gartner Magic Quadrant for Augmented Data Quality Solutions.
As enterprise data environments grow more complex and AI adoption accelerates, we believe the future belongs to platforms that combine:
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Augmented data quality
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Master Data Management (MDM)
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Governance automation
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AI-driven, continuous improvement
CluedIn remains committed to building an AI-enabled data management platform that delivers trusted, high-quality, AI-ready data where it matters most.
“We’re proud that CluedIn has once again been recognized in the Gartner Magic Quadrant for Augmented Data Quality Solutions.
Today, organisations anywhere in the world can adopt CluedIn for enterprise-grade Data Quality and Master Data Management, without complexity standing in the way of capability.
We believe the future of data management belongs to knowledge experts within the business, working hand in hand with AI agents acting as first responders in the data flow. These agents analyse new data sources for mapping, matching, quality, and validation, then federate outcomes into evolving policies, contracts, and rules that continuously improve over time.
More than ever, success in enterprise data management requires a deep understanding of the business and supply chain, and the ability to translate that knowledge into an AI-enabled data management engine. That’s exactly what we have built.”Tim Ward, CEO & Co-Founder, CluedIn
Gartner, Magic Quadrant for Augmented Data Quality Solutions, February 2026.
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