US 12,118,019 B1
Smart data signals for artificial intelligence based modeling
Lopamudra Panda, Ghaziabad (IN); Sumit Taneja, Ghaziabad (IN); Sumit Agarwal, Noida (IN); Rashmi Ashrafi, Lake Mary, FL (US); Mustafa Karmalawala, Pune (IN); Saurabh Mittal, New Delhi (IN); Subodh Baranwal, Greater Noida (IN); Gregory Tyler Freeman, Dunwoody, GA (US); Shailesh Giri, Gurgaon (IN); Anurag Arora, Gurugram (IN); and Ajay Tiwari, Noida (IN)
Assigned to ExlService Holdings, Inc., New York, NY (US)
Filed by ExlService Holdings, Inc., New York, NY (US)
Filed on Nov. 29, 2023, as Appl. No. 18/523,876.
Claims priority of application No. 202311026580 (IN), filed on Apr. 10, 2023.
Int. Cl. G06F 16/00 (2019.01); G06F 3/04817 (2022.01); G06F 16/2457 (2019.01); G06F 16/28 (2019.01); G06Q 40/08 (2012.01)
CPC G06F 16/285 (2019.01) [G06F 3/04817 (2013.01); G06F 16/24573 (2019.01); G06Q 40/08 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method executed by a smart data signals platform for artificial intelligence/machine learning (AI/ML)-based simulation and modeling, the method comprising:
receiving, by a data enrichment engine from a first source computing system, first structured input data comprising claim data;
receiving, by the data enrichment engine from a second source computing system, an unstructured input data comprising at least two of a call note, a claim note, an email, and a policy document;
structuring the unstructured input data to generate second structured input data, wherein the second structured input data comprises a set of tokens generated based on the unstructured input data;
linking, by the data enrichment engine, the first structured input data and the second structured input data to generate an enriched dataset comprising a set of metadata, wherein at least one item in the set of metadata corresponds to at least one token in the set of tokens;
validating, by the data enrichment engine and based on a rule associated with a particular target computing system, the enriched dataset;
performing, by a trigger engine, operations comprising:
evaluating the enriched dataset against a criterion associated with a hypothesis; and
based on a result of an evaluation, generating an electronic trigger signal; and
deploying the electronic trigger signal in connection with the target computing system;
performing, by a trained artificial intelligence (AI) decision engine, operations comprising:
using the electronic trigger signal, generating an analysis dataset;
executing a trained machine learning model on the analysis dataset to generate a resource degradation indicator;
binding the resource degradation indicator to the analysis dataset; and
transmitting the analysis dataset to the target computing system.