New module blends AI agents with human-in-the-loop oversight to fix data faster — improving accuracy, governance, and ROI of AI initiatives

Tamr, the only AI-native master data management (MDM) solution, announced Curator Hub, a new module that helps organizations rapidly tackle the trickiest quality issues in their data — and prepare it for successful generative AI use — by pairing intelligent agents with human expertise.

As data quality becomes the biggest barrier to trustworthy AI, Curator Hub offers a smarter, more scalable way to resolve inconsistencies, fill gaps and connect related records. Teams can work faster; reduce manual effort; and make better, data-driven decisions, while seeing greater returns on AI initiatives.

Tackling Data Challenges with Agentic Curation

In contrast to rules-based approaches, Tamr’s machine learning automates the bulk of the often-onerous data mastering process: unifying, cleaning and enriching enterprise data at scale. Still, the “last mile” of data curation, or about 5% of cases, has remained notoriously hard to resolve automatically. Edge cases, inconsistent values and uncertain matches — like determining whether “Java Town” and “JavaTown Café” refer to the same entity — often require human judgment and eat up valuable time, or simply remain unaddressed.

These data issues add up. Multiple studies have shown that poor data quality costs organizations millions of dollars per year. In addition, according to Gartner® research, “through 2026, 30% of generative AI (GenAI) projects will be abandoned after proof of concept, due to poor data quality, inadequate risk controls, escalating costs or unclear business value.”¹

Curator Hub closes this gap. It marks Tamr’s entry into agentic data curation — the use of LLM-based AI agents that can reason through complex data issues, suggest updates, and explain their logic in plain language. Designed as the “mission control” for human-AI data curation, Curator Hub gives data stewards a central space to manage issues flagged by AI agents or submitted by users.

For CHG Healthcare, a leader in healthcare staffing, this functionality holds strong promise. The company uses Tamr to unify fragmented provider data, reduce duplicates, and enable real-time access to accurate records, and looks forward to building on that success.

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“I’m excited about agentic data curation,” said Taner Maia, senior product manager, provider services platform at CHG Healthcare. “There’s great value in focusing on the curator experience, and Curator Hub and AI agents have real potential to help. As we scale provider onboarding and streamline placement, getting the right data into the hands of the right people even more quickly would be a big win for CHG.”

How Curator Hub Changes the Workflow

That potential becomes clear in the day-to-day work of data stewards. Take the Java Town example earlier: two records with slightly different names and incomplete details. In the past, a data steward would have to track down those records manually, compare fields across tables, and make a judgment call — often without full context or a clear way to see the impact of their decision.

Curator Hub replaces that process with a smarter, more intuitive workflow — shifting from manual data triage to intelligent, human-in-the-loop curation. Through a combination of data quality standards, real-time duplicate checks and background agents, edge cases are automatically flagged in a curated queue, where stewards can:

• See side-by-side comparisons,
• Understand why an issue was flagged, and
• Preview what will change before applying an update

“Curation workflows only work if stewards actually want to use them,” said Paul Balas, Tamr user and data strategy consultant at 303Computing, a consulting firm specializing in enterprise data architecture. “Curator Hub is both intuitive and powerful — surfacing high-impact issues, showing what’s changing, and keeping experts in control without overwhelming them. That’s how you build trust, accelerate adoption, and get more value from your data.”

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Features & Functionality

Curator Hub will be available as part of Tamr’s AI-native MDM platform to all Tamr Cloud customers. It includes a range of features to help teams scale data quality, all within a customizable, user-friendly workspace:

• Prioritized issue queue: Focus on the most pressing problems first. Curator Hub surfaces potential duplicates, missing values and anomalies, ranked by urgency by Tamr’s agents.
• Decision-ready views: See side-by-side comparisons, understand why issues were flagged (with labels and confidence scores), and preview changes before applying updates.
• Golden record refinement: Improve accuracy by moving or reassigning source records to ensure the correct grouping and composition of mastered entities, such as a person or organization.
• Customizable workflows: Define how issues are routed, when agents are triggered, and which cases require human review.
• Transparent curation history: Track who made what changes and when, helping teams audit decisions and maintain data governance.
• System health insights: See resolution progress, monitor issue volume, and visualize data quality trends in real time.
• Built-in (and expanding) agent library: Tap into a starter set of prebuilt AI agents, with more on the way, including industry-specific tools and reusable logic templates.
• Bring Your Own Agent (BYOA): Integrate your custom-built agents into Tamr’s workflow using a supported low-code approach.

“Data projects lose momentum and value when results take too long to materialize,” said Anthony Deighton, CEO of Tamr. “Curator Hub changes that, giving stewards an intuitive way to see, make and explain data improvements. It also provides an important vehicle for leveraging AI agents to automate and improve data curation efficiency — representing a pivotal shift in how organizations can build trust in their data and realize greater returns from downstream AI applications.”

Curator Hub is part of Tamr’s broader mission to bring clarity to enterprise data by combining machine intelligence with human expertise. By helping teams review, approve, and trust the work of AI agents, Tamr is redefining how organizations scale and govern their most valuable data assets.