Audience
Organizations looking for a powerful Data Matching solution
About Kalinda
Legislative controls over what information can be shared and under what circumstances. Data matching and discovery to accelerate information sharing between agencies regarding investigations into specific cases. The heart of the Kalinda system is a powerful machine-learning based algorithm to match person records between multiple agencies based on personal characteristics (such as name, date of birth, etc) and the characteristics of related people. In-depth investigations often require the ability to explore relationships between people or with locations when there is only partial information available. Kalinda is able to answer partial-match queries over person, location and relationship information. Kalinda offers extended algorithms to search for records that are similar to the matched records based on probabilistic record matching.
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Company Information
Kalinda
Australia
www.factil.io/products/kalinda/
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LinkageWiz
Powerful Probabilistic Data Matching algorithms are used, using common identifiers such as name, date of birth, sex, address, SSN, business name and many others. Data can be imported from a wide range of desktop and corporate database systems. Data matching software will enable the detection of up to 99% or higher of all potential matches. For business this can represent considerable extra potential revenue or cost savings, increased fraud detection and, for medical research can mean the difference between a successful research project and one that failed to report any significant findings. LinkageWiz is fast, user friendly and represents outstanding value as it bundles many of the features provided by many other separate products into a single stand-alone package.
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Match2Lists
Match2Lists is the fastest, easiest and most accurate way to Match, Merge and De-duplicate your data. With Our Match2D&B option, you can enrich your data with Dun & Bradstreet information on-demand. In just minutes, you can cleanse your data of duplicates and blend raw data from different sources into powerful information. Our first objective is maximum match results for our customers. Prior to creating Match2Lists, we ran analytics and data visualisation companies and used most "fuzzy" matching software on the market. Unsatisfied by their low match results, we spent 10 years developing the most advanced data matching logic. Our second objective is time: enable our customers to spend less time matching and cleansing data and more time analysing and executing. So we implemented our advanced matching logic on the fast in-memory cloud computing architecture we could find, capable of matching 200 million records in 30 seconds.
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Senzing
Senzing® entity resolution API software provides the most advanced, affordable, and easy-to-use data matching and relationship detection capabilities available. With Senzing software, you can automatically resolve records into common entities in real time as new data is received. The complete view of all records related to every person or organization, across all of your internal and external data sources, can help you reduce costs and enable new revenue opportunities. Companies use Senzing entity resolution API to provide highly accurate views of people, organizations, and their relationships. You can deploy the Senzing entity resolution API on premises or in cloud-native deployments. Data remains in your ecosystem and never flows to Senzing. A free proof of concept can be completed in one day on AWS or on BareMetal. Senzing makes human-intelligent decisions without any pre-training or pre-tuning.
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matchit
The foundation of our matching software, matchit® is designed specifically to deliver results that mirror human-like perception, at scale and without preprocessing. Using Artificial Intelligence, a proprietary phonetic algorithm, lexicons, and a contextual scoring engine, matchit defeats the errors, inconsistencies, and challenges commonly found in contact and business data. Conventional matching solutions require a user to define matching logic, which is a combination of functions and off-the-shelf fuzzy algorithms, used to produce an alphanumeric value. This alphanumeric value, or ‘match key’, forms the basis for comparing two records together and ultimately finding matches. Unlike conventional matching solutions, matchit doesn’t rely on a single comparison between match keys to find a match. Instead, matchit evaluates records contextually, running a variety of comparisons and scoring them individually to grade similarity between all the relevant elements that make up your data.
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Product Details
Platforms Supported
SaaS
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