Entity Matching at
Massive Scale

High-performance entity matching engines for enterprises. Find records across disparate data sources that refer to the same customer, company, product, or supplier.

One person as three systems record him: Daniel J. Reyes, Dan Reyes and D. Reyes, at Northwind Inc., Northwind, Inc. and Northwind Corp., with the phone in two formats and missing from billing. Matching gives back one record: Daniel Reyes, Northwind Inc., +1 512 555 0147.

CRM

Daniel J. Reyes

Northwind Inc.

(512) 555-0147

Billing

Dan Reyes

Northwind, Inc.

—

Support

D. Reyes

Northwind Corp.

+1 512 555 0147

Daniel ReyesNorthwind Inc.+1 512 555 0147

Our latest performance breakthrough
30× faster
Records matched in under 3 hours
1 billion
Computing cost for that workload
< $100

Fragmented data. Connected entities

Your systems often describe the same entity in different ways. Names vary. Fields are incomplete. Records do not line up.

Relixa identifies which records refer to the same entity. Use those matches in your data integration, customer data, and analytics workflows.

Entity matching, built for scale

Relixa makes large-scale entity matching faster, more accurate, and more affordable.

  • Up to 30× faster entity matching
  • Accurate matching across messy, disparate data
  • Billion-record scale at remarkably low cost
Explore our products

A stronger foundation for enterprise data and AI

  1. MDM & Customer 360

    Connect records about the same entity to support unified customer and business views.

  2. Data integration

    Find corresponding entities when bringing together data from different systems.

  3. Knowledge graphs

    Recognize shared entities across sources as a foundation for connected knowledge.

  4. Analytics & AI

    Help analytics and agents work with data that connects the right records.

Deep research. Real enterprise experience

Our team includes leading researchers who have spent more than 15 years advancing entity matching.

We bring together scientific expertise and practical experience turning research into enterprise technologies.

15+
Years of research and engineering in entity matching.
Proven
Publications, awards, startups, and a successful acquisition.
Applied
Earlier technologies developed by team members have been deployed at enterprises.

What do you need to match?