Device for the intelligent encapsulation of legacy data information systems with integrated artificial intelligence

Abstract

Device for the intelligent encapsulation of legacy data information systems with the integration of artificial intelligence, comprising: a collection unit for legacy interfaces, configured to intercept communication data from existing platforms; a semantic interpretation unit designed to analyze and map data structures and process semantics; a contextual abstraction layer designed to convert interpreted information into standardized, interoperable formats; a policy-driven management module that ensures secure access, Data transformation and regulatory compliance are ensured; and a learning and inference unit for adaptive optimization of data mappings and operational logic.

Description

AREA OF INVENTION

[0001] The present invention relates to the modernization of digital systems. More precisely, it relates to a device and an intelligent integration system for enveloping existing information technology infrastructures with an adaptive, artificial intelligence-based layer that provides semantic interpretation, interoperability, and process optimization without altering the core operating code of existing legacy systems. BACKGROUND OF THE INVENTION

[0002] Organizations continue to rely on long-established software environments, such as early generation database systems, mainframe applications, or rule-based enterprise systems that were developed before the introduction of modern data exchange standards.

[0003] Updating these environments often requires extensive code revisions or a complete replacement of the systems, resulting in high costs, long downtimes, and significant operational risks.

[0004] Traditional middleware and interface programs are limited to syntactic data translation and lack the ability to interpret the contextual meaning of legacy data structures. Existing automation tools cannot dynamically adapt to changing workflows or business semantics.

[0005] Therefore, there is a need for a comprehensive device that creates an intelligent encapsulation environment around existing information systems. Such a device should provide a secure, learning-based intermediary layer capable of interpreting, transforming, and optimizing legacy data and control flows using artificial intelligence principles, while operating without invasive changes to the original software architecture. Summary of the invention

[0006] The present invention relates to a device designed to establish an intelligent integration layer around existing legacy data information systems.

[0007] The device includes: a collection unit for legacy interfaces, configured to monitor data exchange processes of existing systems via passive connections and replicated; a semantic interpretation unit that analyzes and maps historical protocols, file structures, and transaction semantics; a contextual abstraction layer that transforms the interpreted information into standardized, interoperable data schemas; a policy-driven management module that ensures security, access control, and compliance during data transformation; as well as a learning and inference unit that continuously refines assignments using artificial intelligence algorithms running on integrated computing hardware.

[0008] The device functions as a self-contained, adaptive integration system capable of connecting legacy software environments with modern applications without requiring recoding. It enables modernization through semantic understanding, autonomous optimization, and secure data transformation. Detailed description of the invention; Overview of the device

[0009] The device is designed as a modular hardware-software system positioned between existing legacy data servers and modern applications. It includes data acquisition interfaces, computational logic for semantic processing, memory for transformation rules, and secure communication channels. Acquisition unit for legacy interfaces

[0010] This unit intercepts input and output data streams from legacy systems. It uses signal replication and data mirroring techniques to capture operational information without affecting the functionality of the underlying systems. The capture process ensures complete operational continuity for the original software. Semantic interpretation unit

[0011] The semantic interpretation unit performs an automated analysis of the collected data.

[0012] It extracts entities, identifies relationships, and determines logical dependencies between data elements of the legacy systems.

[0013] The unit creates an evolving internal knowledge structure that reflects the operational logic and business significance.

[0014] It uses deterministic rule sets in combination with machine-learned semantic mappings to enable precise interpretation of different legacy data formats and undocumented system behaviors. Contextual abstraction layer

[0015] The contextual abstraction layer standardizes the interpreted data into modern, interoperable representations.

[0016] It provides a normalized data schema that is accessible via controlled communication interfaces such as standardized data services or structured messaging channels.

[0017] This layer also performs validations, consistency checks, and traceability of data origins to ensure reliability and traceability. Policy-driven administration module

[0018] This module enforces governance and security protocols.

[0019] It defines user permissions, encryption standards, and auditing mechanisms. Access requests from modern applications are checked against these guidelines before any transformation or data exchange takes place. Learning and inference unit

[0020] This unit performs adaptive learning functions on integrated computing hardware. It analyzes performance metrics, feedback from connected systems, and error corrections to refine the transformation rules.

[0021] The unit uses general artificial intelligence algorithms implemented via configurable logic circuits or parallel processing units. It operates locally to protect the confidentiality of company data while enabling continuous optimization. Visualization and control interface

[0022] A user interface is provided through which administrators can configure operating parameters, monitor data transformation, and view audit logs for policy compliance.

[0023] The interface displays visual representations of the system diagrams as well as performance indicators. Operational process 1. The data acquisition unit for legacy interfaces collects transaction data. 2. The semantic interpretation unit analyzes and categorizes the data. 3. The contextual abstraction layer generates standardized representations. 4. The policy-driven management module verifies the transformation processes. 5. The learning and inference unit refines the processing based on the results. 6. The output is transmitted to modern applications via secure channels.

[0024] This process enables a progressive modernization of information systems without interrupting or changing the original legacy data software.