Upgrade Your Fuzzy Name Matching

Rosette is trusted by the world’s largest and most critical banking and security systems.

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Percentage of correct matches testing against a dataset with 7,571 person names, with at least 10 variants for each name.

✓ Enhance your current system

✓ Machine learning algorithms

✓ Scalable

✓ Explainable

✓ Flexible deployment options

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See Rosette in action

Learn how our algorithm works and the underlying capabilities that allow for a readable and accurate score.


  • Reduce false positives — When a name is erroneously matched to a watch list record, time and money is wasted in manually following up on each hit
  • Reduce false negatives — When a match is missed, your screening system has failed its mission and consequences can be very serious
  • Simultaneously considers 13 name variations including cross-lingual matching in 21 languages — including Arabic, Cyrillic, and Asian scripts
  • Employs a hybrid of methods including phonetics, rules, deep learning, and statistical models
  • Special algorithms for more accurate Chinese and Japanese organization name matching.


  • Slow systems get ignored, ensure your organization does a thorough check of every name by deploying Rosette
  • Consistent response time for long or short names; names with two components or more than five
  • User configurable to increase speed or recall to meet the needs of your task or data.

Active development

  • At least six software releases per year
  • Fast response to support requests.


  • Deploys as a plugin to Elasticsearch, Solr, or via cloud or on-premise (SDK or server)
  • User configurable and tunable to dataset characteristics
  • Confidence score produced for each match, ability to weight any number of other identity attribute fields.

“…answering, ‘Is that the same person or not based on a name?’ is subjective, and the amount of time for a human can vary greatly, and accuracy varies greatly. That’s where being able to apply sophisticated software makes a huge difference.”
— Nathaniel Palmer, Chief Architect at Serco, on name matching for applications to the Affordable Care Act

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