Vertex AI Agent Builder for Regulated Environments
DOI:
https://doi.org/10.63282/3117-5481/AIJCST-V6I2P106Keywords:
Vertex AI, Agent Builder, Regulated Environments, Data Governance, AI Compliance, Responsible AI, Federated Learning, Explainability, Cloud Security, Model Governance, Auditability, Transparency, Privacy Preservation, Human-in-the-Loop, Policy Enforcement, Risk Management, AI Scalability, Google Cloud PlatformAbstract
Healthcare, government, and financial sectors have tried to use A.I. their efforts met with various difficulties in compliance, data governance, and explainability, among other issues. The company does not only deliver a powerful and expandable infrastructural framework for building A.I. systems that are regulation-compliant through the use of Google's Vertex AI Agent Builder but also retains its agility. Transparency, auditability, and policy compliance are the features that organizations can build into AI agents with the Vertex AI environment. The environment supports model management, explainable AI (XAI), and data lineage. The architecture given describes onboard data processing, differential privacy, and human-in-the-loop governance in modular pipelines. These pipelines managed by Agent Builder, and Cloud Audit Logs are there for traceability by providing support. The system's architecture, therefore, becomes the main driver for compliance effectiveness, accountability, and trust, thus enabling companies to be in a position to accelerate the responsible AI deployment without compromising their compliance obligations. The paper, therefore, suggests further investigation of interoperability, continuous risk monitoring, and policy harmonization across different regulatory frameworks. It points out the significance of Vertex AI Agent Builder as an enabler for the scaling of compliant AI.
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