Peer-reviewed papers
4 papers Accepted 2026
Agentic Artificial Intelligence for Enterprise Customer-Relationship Platforms
CML 2026 — International Conference on Machine Learning Applications
Peer-reviewed conference on applied machine-learning systems. Paper accepted under reference number 1346.
CML 2026 Paper #1346 Investigates how multi-agent LLM architectures can be safely embedded inside regulated enterprise CRM workflows, with particular attention to identity, tool-access control, audit, and model-risk governance. Frames the operating boundaries an enterprise architect must define when an autonomous AI agent participates in customer-facing systems.
Agentic AIEnterprise CRMModel-risk governanceMulti-agent orchestration
Accepted 2026
Continuous Integration and Delivery Patterns for Regulated Financial-Services Platforms
SCI 2026 — International Conference on Smart Computing & Informatics, Vietnam
Peer-reviewed international conference; paper accepted for publication in the conference proceedings.
Examines CI/CD pipeline architectures for production enterprise platforms operating under SOX, FINRA, and SEC controls. Synthesises lessons from large-scale Salesforce and AWS deployments inside a Global Systemically Important Bank, with particular focus on segregation of duties, automated control evidence, and audit traceability.
CI/CDRegulated software deliverySalesforce DevOpsAudit & compliance
Submitted 2026
Self-Healing Infrastructure-as-Code for Enterprise Cloud Platforms
International Journal of Data Science (IJDS) — Growing Science
Peer-reviewed open-access journal in the data and decision sciences. Paper under editorial review.
Proposes a self-healing infrastructure-as-code framework in which provisioning, drift detection, and remediation are coordinated by autonomous control loops with explicit governance gates. Evaluates the framework against multi-cloud deployments inside a regulated financial institution.
Infrastructure as codeSelf-healing systemsCloud operationsReliability engineering
Under Review 2026
Human-Machine Collaboration in AI-Augmented Enterprise Architecture
IEEE Transactions on Human-Machine Systems (THMS)
Long-running IEEE peer-reviewed journal on the design, evaluation, and operation of systems involving humans interacting with intelligent machines. Manuscript under review.
Investigates how enterprise architects increasingly co-design with agentic AI systems, treating the model as a collaborator inside the architecture loop rather than a tool. Establishes a taxonomy of human-machine handoffs in enterprise architecture practice.
Human-machine systemsAI-assisted architectureEnterprise architecture practiceCognitive ergonomics
About this page
This page surfaces only formal scholarly venues and major-trade publications. Long-form essays, walkthroughs, and Medium posts are catalogued separately on the Writing page.