Citigroup. has been granted a patent for a system that updates rule engines during software development. It utilizes generated proxy models with predefined deployment criteria to assess when to replace existing rule engines, focusing on factors like efficiency and scripting language comparisons. GlobalData’s report on Citigroup gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on Citigroup, was a key innovation area identified from patents. Citigroup's grant share as of June 2024 was 85%. Grant share is based on the ratio of number of grants to total number of patents.
Model deployment criteria for updating rule engines
The patent US12045610B1 outlines a system and method for updating rule engines during software development by utilizing generated proxy models that adhere to predefined deployment criteria. The system comprises processors and non-transitory computer-readable media containing instructions that facilitate operations such as retrieving existing rule engines, determining model deployment criteria, and extracting scripts from these engines. An artificial intelligence model is employed to modify the extracted scripts based on historical comparisons of scripting languages and their efficiencies. The modified rule engine processes input data to generate outputs, which are then compared to outputs from the original rule engine to assess differences. This comparison informs the decision on whether to deploy the modified rule engine based on the established deployment criteria.
The method further details specific processes for determining the efficiency of scripting languages, including compatibility and performance characteristics. It also includes steps for optimizing script length and replacing hard-coded values with named constants. The patent emphasizes the importance of validating the modified scripts against syntax and dependency criteria. Additionally, it outlines how to quantify differences between outputs, such as error counts and performance metrics, to ensure that the modified rule engine meets or exceeds the performance of the existing engine before deployment. Overall, the patent presents a structured approach to enhancing rule engines, leveraging AI for script modification and ensuring compliance with deployment standards.
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