ERROR PROOF SOLUTION FOR COMPLEX LEGACY TO DISTRIBUTED COMPUTING TRANSFORMATION IN FINANCIAL SERVICES AND HEALTHCARE USING PREDICTIVE AI MODELS & GENAI

Abstract

The present invention provides an error-proof solution for migrating complex legacy systems to distributed computing environments, specifically in the financial services and healthcare sectors. The solution leverages predictive AI models and generative AI (GenAI) to forecast potential migration errors and automatically generate real-time corrective actions. The system includes a legacy system analyzer to assess existing infrastructure, a predictive AI engine to identify risks, and a GenAI engine to produce tailored solutions for issues such as data inconsistencies, compatibility, and performance degradation. By automating the migration process, the invention ensures system compatibility, minimizes downtime, and enhances operational efficiency, enabling a seamless transition to modern distributed architectures while maintaining regulatory compliance and data integrity.

Specification

Description:The embodiments of the present invention generally relates to the field of information technology, specifically to the transformation of complex legacy systems in industries such as financial services and healthcare into distributed computing architectures. More particularly, the invention provides an error-proof solution using predictive artificial intelligence (AI) models and generative AI (GenAI) to streamline the migration process, ensuring seamless integration, system compatibility, and minimized operational disruptions during the transition from legacy to distributed systems.
BACKGROUND OF THE INVENTION
The following description of related art is intended to provide background information pertaining to the field of the disclosure. This section may include certain aspects of the art that may be related to various features of the present disclosure. However, it should be appreciated that this section be used only to enhance the understanding of the reader with respect to the present disclosure, and not as , Claims:1. A method for error-proof legacy system transformation to a distributed computing environment in financial services and healthcare, comprising:
performing an initial assessment of a legacy system using a legacy system analyzer to identify potential migration issues;
predicting potential migration errors using a predictive AI engine, based on historical data and system performance analysis;
generating real-time solutions to the predicted errors using a generative AI (GenAI) engine;
executing the migration process using the generated solutions to ensure compatibility, data integrity, and minimal disruption in the distributed computing environment.

2. The method of claim 1, wherein the legacy system analyzer performs an evaluation of software dependencies, hardware resources, data flow patterns, and system performance to generate a comprehensive system assessment.

3. The method of claim 1, wherein the predictive AI engine utilizes machine learning models trained on historical migration data to predict errors

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