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Identity Resolution 
Made Easy and Accurate


Welcome to EntityWise

Our Platform

Built on advanced Machine Learning technology, our approach is more accurate than the older probabilistic and deterministic approaches.




Duplicates are more than one unique identity (person, company, product) that exists in a single source.  Our technology can find more duplicate identities than any other platform.

Unified View

Identifying a unique identity across multiple sources is critical to a thorough understanding of your identity (person, company, product) and our technology can unify any view required.


Searching an identity successfully (person, company, product) within a source or across sources can be the difference in efficient operation.  Our technology can find identities across any number of sources.

Why is our accuracy better than the others?

Because we solve the tasks/potential duplicates on the other platforms that they cannot solve themselves.
Epic, IBM, Cerner, Informatica, Meditech, Nextgate, Reltio etc..., attempt to match the data but fail to match it all and create tasks (also called Potential Duplicates/Matches).
Because they fail to match it all, they create tasks which are left for people to resolve manually.

We help clients solve these tasks on the these platforms.

Example 1:  We helped a hospital resolve 380,000 Epic Potential Duplicates (380,000 pairs Epic couldn't match) in a few weeks saving their team 18 months of manual review.

Example 2:  We helped a hospital resolve 240,000 Tasks on the IBM MDM platform (240,000 Pairs IBM couldn't match) in a few weeks saving them $323,000 (according to their management)



Our Technology

Match made simple and accurate

Why Machine Learning Is a Better Technology


As experts in match, we have experience in all 3 match technologies; deterministic, probabilistic , and machine learning and we can say that machine learning is by far the best approach to the match problem.

Why Machine Learning is a better approach than the older traditional Deterministic and Probabilistic approaches?   The traditional approaches are linear which means they cannot distinguish like a human.  Machine learning can learn and become a virtual human.

Goal: The number one goal to a match approach is its match accuracy.  But how data is matched is seen differently by each customer which means a custom match approach, tailored to their needs, is an absolute requirement for the best accuracy.   One-size fits all solutions will not achieve the same level of accuracy.

Our Solutions

Explore our capabilities


Data Lake

Goal to create a data lake, Multiple Sources of data within our organization, Sending all sources causes a lot of duplicate records


Identity Resolution

Records exist in many different sources , Not a full picture of my Patient, Customer, Account or Opportunity


HealthCare Cleanse

MPI Cleanups (Deduplication) and resolving potential duplicates (tasks, suspects, reviews) are of the highest importance.



Customer has right to understand the information you posses, Customer has the right to be “forgotten”

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