What Makes Tamr AI-Native?

Editor’s Note: This post was originally published in March 2025. We’ve updated the content to reflect the latest information and best practices so you can stay up to date with the most relevant insights on the topic.

Tamr is taking an AI-native approach to master data management (MDM). And it’s not only disrupting—but also fundamentally changing—the MDM category.

With 19+ patents to our name, Tamr uses AI in unique and proven ways to efficiently and scalably solve really difficult data quality problems faced by organizations today. And this approach isn’t new to Tamr. Since its founding, the company has been dedicated to developing AI-based technology that stands as proof of our commitment to innovation.

AI-Native MDM vs. Traditional MDM

Tamr’s foundational use of AI stands in sharp contrast to traditional MDM solutions. Instead of relying on outdated technology and an extensive use of rules for data mastering, Tamr thoughtfully and strategically designed its solution with purpose-built AI technology at the core. Our architecture, workflows, and user interfaces are all built around AI, an approach that is fundamentally different from what legacy MDM providers do. 

While many traditional MDM solution providers say they are AI-powered, take a closer look and you’ll see that, in reality, these providers are simply bolting on commercially available large language model (LLM) features around the edges. This approach is very different to the way Tamr embeds AI at the center of the data mastering process. And it’s this AI-native approach that makes Tamr fast, easy, and efficient, producing significantly superior outcomes as compared to slow, costly, unreliable, and difficult-to-use traditional MDM solutions. 

Tamr: AI-Native to the Core

Automating the central aspects of MDM with AI is what sets Tamr—and our AI-native approach—apart from traditional MDM solutions, enabling us to deliver massive efficiency and scalability. 

Tamr’s six principal AI features and benefits include:

• Entity Resolution: Tamr’s advanced AI models and optimization techniques use machine learning (ML) clustering to match, link, and de-duplicate records across data silos, making the typically formidable challenge of entity resolution fast and easy. Tamr assigns unique IDs to each group of records and then, uniquely and importantly, Tamr versions these links over time to provide an effective audit trail and a map to the original data sources. 

• Data Mastering at Scale: Tamr has trained AI to perform critical data mastering and curation tasks including schema mapping, data cleaning and standardization, match verification, data enrichment, and golden record creation. Using proven, patented ML to perform these tasks enables organizations to implement data mastering programs extraordinarily fast (think days or weeks, not months or years), at lower cost, and with better results than traditional methods that rely on static, brittle, rules-based MDM tools and require manual efforts by large teams. 

• Semantic Search: Tamr’s AI-powered semantic search functionality enhances data discovery by understanding meaning, intent, and context, rather than relying on exact keyword matches. It resolves inconsistencies across terminology and languages, ensuring users find relevant data in the moment. Leveraging deep learning, LLMs, and feedback-driven refinement, it continuously improves, delivering smarter, more precise search results that minimize duplicates and drive better decisions and efficiency.

• Search Before Create: Tamr has AI that works in the background to prevent users from creating bad data as they work in operational systems. Available as one of Tamr’s real-time APIs, this functionality ensures every new record added to your systems is accurate, consistent, and connected to the broader data ecosystem.

• Agentic Data Curation: Tamr makes LLM-based AI agents available to automate even more of the data curation process. Addressing the “last mile” challenge of resolving the more complex edge cases that traditionally require human intervention, Tamr’s agentic curation capability allows data stewards to capture and act on the contextual insights needed to make confident decisions around the most difficult data scenarios. 

• LLM Connectivity: Tamr’s AI provides LLMs with secure, governed access to golden records, entity relationships, and links between data sources, giving these generic models the context needed to be much more useful in practice. Using Tamr’s MCP Server, users and AI agents can pose sophisticated questions of an organization’s trusted data in Tamr and receive immediate, actionable answers.

In addition to these AI features and benefits, three core elements underpin all of Tamr’s AI functionality: a secure, scalable, battle-tested SaaS infrastructure, highly tuned data products that address numerous use cases, and continuous model training that keeps getting better and better at solving the master data management challenges facing organizations today. 

Download our ebook, How Agentic Data Curation is Transforming Data Mastering: Perspectives from the Tamr Co-Founders, to learn about the latest developments in AI-native data management.