Ensuring regulatory compliance with standards such as HIPAA and GDPR for healthcare data integration is always a challenge. This paper presents an AI-based framework for monitoring compliance with Synthetic FHIR Data by Synthea in an integration platform on MuleSoft. The proposed technique uses machine learning to identify the data exchange pattern, recognize abnormalities, and enforce security policies. Utilizing the Synthetic FHIR Data by Synthea, real-world interoperability scenarios in healthcare are simulated to test the efficacy of AI-based monitoring for compliance. Experimental results indicate that AI models can identify potential regulatory violations effectively and enhance the security level of the data. This work determines the potential for intelligent monitoring for compliance with healthcare data integration toward creating secure, efficient, and regulatory-compliant interoperability solutions.