Data Quality Agent
Argano · Operations & Productivity
Certification per Microsoft Marketplace.
Evidence tier Source Confirmed · 7 captures on record
What the publisher says
As described on Microsoft Marketplace.
The Data Quality Agent is an AI-powered solution designed to
proactively identify, resolve, and enrich master data across customers,
Show the rest of the publisher’s description (32 more lines)
contacts, vendors, and products. Operating within Dataverse and integrated via
Microsoft Fabric, the agent uses LLM and machine learning–based fuzzy matching
to detect duplicates and inconsistencies across fragmented and imperfect
datasets.
Beyond duplicate detection, the agent recommends record
merges, data enrichment, and corrective actions for data stewards, transforming
traditionally manual and reactive data management processes into an
intelligent, continuous workflow. It incorporates human-in-the-loop feedback,
learning from steward decisions over time to improve accuracy and reduce false
positives.
Unlike static, rule-based duplicate detection in D365, this
agent introduces adaptive, learning-based intelligence from day one—enabling
organizations to maintain high-quality, trusted data at scale. The result is a
unified, accurate data foundation that enhances operational efficiency and
ensures downstream analytics and AI initiatives are built on reliable
information.
Type of User That Benefits
- Data
Stewards / Master Data Management (MDM) Teams
- Finance
(AP/AR) and Sales Operations Teams
- Customer
Service & CRM Administrators
- Data
& Analytics / IT Leaders responsible for governance
Business Impact
- Create a trusted, unified data foundation by continuously identifying and resolving duplicate and inconsistent records across customers, vendors, products, and contacts.
- Reduce manual data management effort and free teams for higher-value work by automating duplicate detection, record cleanup, and enrichment recommendations.
- Improve operational execution and customer experience by preventing duplicate outreach, incorrect shipments, and inconsistent customer and vendor interactions.
- Increase confidence in reporting, analytics, and decision-making with accurate, unified records that teams can trust across the business.
- Move beyond static rules to adaptive learning-based data quality management with intelligence that improves over time.
- Build an AI-ready data foundation for scalable advanced analytics and automation by establishing clean, enriched, and trusted data across the enterprise.
Preview
2 images
Agent build and provenance
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Compliance
- FedRAMPConfirmedNot listed90%, registry-checkedNo FedRAMP Marketplace entry matched this vendor's domain, checked 2026-08-27registry recordas observed 2026-08-27
Confirmed means matched to a public authoritative registry. Claimed means the vendor or its listing states it, not yet cross-checked. A framework not shown was not found in any source we hold, which is not evidence against it. Not listed means a scoped registry check found no match for this vendor's domain: a No is a scoped registry check, not a compliance judgment. Confidence bands: 95% domain-verified, 90% registry-checked, 80% self-attested, 70% weak signal. Self-attested items marked “vendor's site” are gathered from the vendor's own website and are not verified by us.
Vendor
External enrichment
Sources
Publisher resources
3 linksLinked repositories
Unknown means this listing does not publish a repository. It is not a statement that the code is closed, and a linked repository is not a claim that the publisher wrote it: the registry computes that relationship privately and does not publish it.
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