Tamr Adds Basis Technology to Connect And Enrich Enterprise-Wide Data Across Languages

Unifying databases from multiple business units reveals cost-savings, risk-mitigation opportunities


CAMBRIDGE, Mass. May 12, 2016–Traditionally, to analyze sourcing costs and supplier risk, a procurement department would task a small team armed with spreadsheets to prepare spend data for analysis—which is often siloed in multiple, disparate systems. A month later, the insight would be delivered, but often lacking all of the context a manager would like to see. Tamr has changed all of that. Its human-guided automation software empowers teams to prepare all of their data for analysis—not just some—in a fraction of the time it takes using traditional labor or technology.

Basis Technology announced today that its Rosette® text analytics has been integrated by Tamr, Inc. to overcome the challenges of unifying data in English, Western European, Eastern European, and Asian languages. Tamr’s system will leverage Rosette’slinguistic analysis, entity extraction, and name matching technologies.

“Handling multilingual text is essential to integrating data across languages, and Rosette is unsurpassed in this area,” Nik Bates-Haus, Tech Lead at Tamr, said. “Whether it’s matching part descriptions, brand references, titles, or something else, Rosette breaks down language barriers that would otherwise keep data siloed and enables analytics on data from across the enterprise—regardless of geographic challenges.”

In the data Tamr unifies for domains such as procurement, clinical trials, and customer interactions, names are ubiquitous—and include customers, organizations, locations, suppliers, and employees.

Rosette reveals name matches—within and across languages—that enable Tamr to show probable matches for human subject matter experts to consider. The experts research and verify the correct and incorrect pairings, which then become training data for Tamr. The more data Tamr sees, the better its recommendations become, and the less the experts need to do in the future.

“The fact that Rosette algorithmically understands and matches nicknames, familial names, and more across cultures enables our software to find name matches that it wouldn’t have been able to find,” Bates-Haus said.

The advantages of using Tamr to connect, cleanse, enrich, and classify data from disparate data sources both quickly and cost efficiently are tremendous. Sourcing and procurement analysts use Tamr to identify cost-savings and risk mitigation opportunities within their supply base—which often includes multiple business units. Unified data reveals pricing and payment term discrepancies for components purchased, and using Tamr for enrichment with external data may identify at-risk suppliers based on creditworthiness ratings or other sources of third party risk data.

“Tamr has turned data preparation on its head: with Tamr, as the amount of data grows, the human effort required to organize it actually decreases,” Gregor Stewart, VP of Product Management at Basis Technology, said. “Tamr is exactly the kind of ‘human in the loop’ innovation that we designed the Rosette text analysis platform to enable, and underscores the value of our truly multilingual approach.”

About Basis Technology

For over 20 years, Basis Technology has been a pioneer in machine learning and natural language understanding. The Rosette® platform, accessible on premise or as a web API, gives businesses and government agencies around the world the necessary interoperable linguistic tools for deep knowledge decision-making. We work with companies large and small who build applications spanning social media monitoring, risk and compliance, identity management, and security scanning. The Rosette platform adds a wealth of powerful functionality—from pure linguistics to analyses centered around entities, names, and relationships in Asian, European, and Middle Eastern languages—to any underlying search or database infrastructure.  For more information, email or visit

About Tamr, Inc.

Tamr, Inc. simplifies and automates data preparation for spend analytics, clinical data integration, and other business problems, so businesses can ask big questions and get to business insights faster. The Tamr platform combines human insight with machine learning algorithms to unify and prepare data across data silos for analytics. Tamr customers include Amgen, Biogen Idec, Cinch, GE, Merck. Novartis, Roche, Siemens, Thomson Reuters, and Toyota. Based in Cambridge, Mass., Tamr was founded in 2013 by database industry veterans Andy Palmer, Mike Stonebraker, and Ihab Ilyas with George Beskales, Daniel Bruckner, and Alex Pagan.


Basis Technology