AI based vendor and customer agnostic framework to improve integration of legacy systems
Systems and methods provide for integrating legacy systems into a unified platform. Embodiments include a system configured to ingest, normalize, and store data from multiple sources using a data layer, analyze and transform data using AI algorithms by a processing layer, and provide a dynamic user interface for data visualization and interaction by a presentation layer. Methods are provided for receiving, by a computing device, data such as email orders, vendor catalogs, CRM data, etc., extracting data from the content, processing the data using natural language processing techniques, analyzing the data using machine learning models, mapping the data to a unified platform's schema, managing the integration workflow using a workflow orchestration engine, providing real-time data insights, and resolving data errors or anomalies using an exception management system.
1 . A system for integrating legacy systems into a unified platform, comprising:
a server, coupled to a processor, and configured to execute instructions that:
ingest, normalize, and store data, by a data layer, from multiple sources;
analyze and transform data using AI algorithms, by a processing layer,
wherein the processing layer comprises a self-learning generative AI engine configured to automatically identify, without predefined mappings, a schema of a legacy system by applying
(a) natural language processing to extract relevant information from a plurality of data fields comprising one or more of customer notes, communications, and documents, and
(b) at least one machine learning process to historical structured data to detect patterns and relationships within the data fields,
wherein the generative AI engine employs a schema mapping engine to transform data from the legacy system into a canonical schema of the unified platform through normalization, deduplication, and conversion tasks, and
wherein the generative AI engine preserves the original schema for bidirectional interoperability to enable the legacy system to continue operating in its native format without modification; and
present a dynamic user interface for data visualization and interaction, by a presentation layer;
wherein the processing layer comprises an AI and analytics module featuring a self-learning AI engine that continuously adapts integration processes based on new data and user interactions.
2 . The system of claim 1 , wherein the data layer comprises connectors and APIs to facilitate data extraction from legacy systems such as ERP, CRM, and CPQ, supporting multiple data formats and communication protocols.
3 . The system of claim 1 , wherein the data layer comprises preprocessing units that clean and standardize data, employing techniques such as tokenization, stemming, lemmatization, scaling, and transformation.
4 . The system of claim 1 , wherein the processing layer comprises a workflow orchestration engine that manages integration workflows facilitating data flow between legacy systems and the unified platform.
5 . The system of claim 1 , wherein the presentation layer comprises customizable dashboards that provide real-time data insights and interactive visualizations such as charts, graphs, and heat maps.
6 . The system of claim 1 , wherein the presentation layer comprises security features such as role-based access controls, secure login mechanisms, and data encryption both in transit and at rest.