Reltio today released the 2023.2 version of its flagship Connected Data Platform, infusing more artificial intelligence (AI)-powered capabilities to help enable enterprises with master data management (MDM) operations.
The Reltio Connected Data Platform provides organizations with MDM capabilities, which are increasingly critical for business operations, analytics and AI. The idea behind MDM is that there is a master record, sometimes referred to as the “golden record,” for a given data entry. That entry could be a user name, address, product or other data attribute that needs to be accurate. With data coming from multiple sources, there can be discrepancies that need to be resolved, in a process known as entity resolution.
With the 2023.2 update, Reltio is introducing AI-powered entity resolution that uses the power of large language models (LLMs) to help solve the challenge.
“AI, especially with the evolution of the large language models, makes a lot of sense because a lot of the disambiguation requires knowledge of other aspects that may or may not be part of the data itself,” Manish Sood, founder and CEO of Reltio, told VentureBeat.
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In the past, Reltio relied on rule-based and algorithmic approaches for entity resolution.
Sood explained that the rule-based approach involved attempting to define all the different permutations and combinations in order to compare records. The logic for the rules was often hand-coded, and he noted that the number of permutations tended to be fairly large.
For example, there is a need to understand the complete vocabulary of nicknames that exist across every language, for every person’s name and translations of those names. “That’s a vast amount of data that you have to look at and then build in as a part of the algorithmic capabilities,” Sood said.
“But now instead of trying to do it by brute force, we are able to do it by training large language models to be able to understand and be aware of such permutations and combinations that can be brought to the front as a part of the comparison process that we run.”
The AI models are trained on a variety of data sources, including public information relevant to specific industries like life sciences and healthcare. This domain-specific training helps the models better resolve entities within those industries.
Reltio is using LLMs from cloud providers like AWS, Google Cloud and Azure to power the AI capabilities for training and delivering entity resolution.
>>Don’t miss our special issue: Building the foundation for customer data quality.<<
Beyond entity resolution, Reltio is using AI for other functions, both in its product platform and as part of its overall internal engineering.
Sood said that Reltio is working on integrating AI to help improve data quality. The functionality will provide recommendations and automatically suggest fixes to data.
“The type of work that we’re doing reduces or takes out a lot of the manual effort that customers have to apply to constant data curation, and that is the direction that you will see coming up in the next few releases,” Sood said.
Producing the “golden record,” the definitive source of truth for a given data point, has always been foundational to MDM. It’s a challenge that has only become more complex with the growing volume of data and the increasing use of AI. Without trusted data, Sood said that AI is more likely to end up with a “garbage in, garbage out” type of outcome.
“AI is bringing the focus more so than ever before to a trusted data foundation,” he said.
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Reltio today released the 2023.2 version of its flagship Connected Data Platform, infusing more artificial intelligence (AI)-powered capabilities to help enable enterprises with master data management (MDM) operations.
The Reltio Connected Data Platform provides organizations with MDM capabilities, which are increasingly critical for business operations, analytics and AI. The idea behind MDM is that there is a master record, sometimes referred to as the “golden record,” for a given data entry. That entry could be a user name, address, product or other data attribute that needs to be accurate. With data coming from multiple sources, there can be discrepancies that need to be resolved, in a process known as entity resolution.
With the 2023.2 update, Reltio is introducing AI-powered entity resolution that uses the power of large language models (LLMs) to help solve the challenge.
“AI, especially with the evolution of the large language models, makes a lot of sense because a lot of the disambiguation requires knowledge of other aspects that may or may not be part of the data itself,” Manish Sood, founder and CEO of Reltio, told VentureBeat.
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From rule-based algorithms to AI-powered entity resolution
In the past, Reltio relied on rule-based and algorithmic approaches for entity resolution.
Sood explained that the rule-based approach involved attempting to define all the different permutations and combinations in order to compare records. The logic for the rules was often hand-coded, and he noted that the number of permutations tended to be fairly large.
For example, there is a need to understand the complete vocabulary of nicknames that exist across every language, for every person’s name and translations of those names. “That’s a vast amount of data that you have to look at and then build in as a part of the algorithmic capabilities,” Sood said.
“But now instead of trying to do it by brute force, we are able to do it by training large language models to be able to understand and be aware of such permutations and combinations that can be brought to the front as a part of the comparison process that we run.”
The AI models are trained on a variety of data sources, including public information relevant to specific industries like life sciences and healthcare. This domain-specific training helps the models better resolve entities within those industries.
Reltio is using LLMs from cloud providers like AWS, Google Cloud and Azure to power the AI capabilities for training and delivering entity resolution.
>>Don’t miss our special issue: Building the foundation for customer data quality.<<
Why MDM needs AI and vice-versa
Beyond entity resolution, Reltio is using AI for other functions, both in its product platform and as part of its overall internal engineering.
Sood said that Reltio is working on integrating AI to help improve data quality. The functionality will provide recommendations and automatically suggest fixes to data.
“The type of work that we’re doing reduces or takes out a lot of the manual effort that customers have to apply to constant data curation, and that is the direction that you will see coming up in the next few releases,” Sood said.
Producing the “golden record,” the definitive source of truth for a given data point, has always been foundational to MDM. It’s a challenge that has only become more complex with the growing volume of data and the increasing use of AI. Without trusted data, Sood said that AI is more likely to end up with a “garbage in, garbage out” type of outcome.
“AI is bringing the focus more so than ever before to a trusted data foundation,” he said.
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Author: Sean Michael Kerner
Source: Venturebeat
