## 1 Introduction
### Significance of the Study  
The advancement of technology has surpassed the proposals intended to address the long-standing issues of EAI from its early years. Moreover, the landscape becomes increasingly complex as emerging technologies drive the development of software systems, giving rise to new integration requirements. This proposal is based on the two significant challenges the EAI faces today: syntactic and semantic integration among enterprise applications at the level of software or data units. One reason is that each department/area built its software systems, making interoperability difficult. It is essential to have a coherent semantic integration approach due to analysis. For this, the architecture proposals currently used continue to use a declarative definition for the data types and formats of the field that will facilitate the exchange of information in the integration configuration. Some challenges for the integration of systems acquired from third parties and legacy systems are scenarios where the legacy system does not have an API (Application Programming Interface) for integration or where, in some legacy systems, you may come across mechanisms for communication via file exchange such as XML (eXtensible Markup Language), CSV (Comma Separated Values) and XLS (Microsoft Excel Spreadsheet file), which are either run manually or run automatically. Research has predominantly concentrated on achieving seamless data exchange among software components [1]. As a result, technological advancements have outpaced the original proposals to address the long-standing issues within EAI since its inception. Furthermore, the landscape is becoming increasingly intricate due to the emergence of new technologies driving the development of software systems. These systems are now widespread across various sectors of society, encompassing a diverse range of business processes, each reliant on distinct software solutions. These solutions are constructed on varying platforms and use cutting-edge technologies, often incorporating multiple data sources that lack inherent interoperability. We illustrated a specific scenario in our prior research [1]. When a client requests a change in the data being sent or the data type within its database schema during a web service invocation, the consumer and the provider must reach a consensus on the message formats. When independent development teams handle the design of these two integration components, reaching an agreement on standard schemas can be challenging. Multiply this challenge by the number of applications employing these services, each with its typical service and software components, and you will understand how negotiating message formats can evolve into a full-time task with significant maintenance costs. Typically, creating these structures involves using XSD (XML Schema Definition) schemas, which define how information travels and gets converted into an XML document during the design phase. This approach establishes loose coupling at the external and data levels. This condition also applies to data entities within databases, JSON (JavaScript Object Notation) structures implemented by REST (Representational State Transfer) APIs, and messages exchanged as in-memory components in scenarios like Queues, MQSeries, Apache Camel, and more. In each case, the information exchange is established during the design phase. Consequently, the need for dynamic EAI solutions has become paramount. The proposal presented in this article aims to address this challenge. It recognizes that dynamic EAI solutions can be effectively achieved by utilizing technologies like SOA (Service-Oriented Architecture) web services and contemporary approaches such as REST microservices. One notable advantage of these emerging technologies is their capability to facilitate low-level integration, thereby improving application data exchange. Consequently, this approach fosters interoperability by enabling a controlled and efficient data flow.