Data Centric Cybersecurity models for large scale Insurance Systems

As insurance platforms become data-driven, protecting sensitive policyholder and claims data must be embedded at the data layer—not just the network perimeter. This session outlines a data-centric cybersecurity model that combines zero-trust principles, AI-driven anomaly detection, and continuous data classification to safeguard high-volume insurance ecosystems. We will highlight how encryption, tokenization, and real-time monitoring reduce breach impact, ensure regulatory compliance (e.g., HIPAA, NIST), and enable secure AI adoption. The approach shifts security from reactive controls to proactive, intelligence-led protection—delivering resilience, trust, and measurable risk reduction across enterprise insurance operations.

AI for Protecting Patient Data (PHI Security)

As healthcare data grows in volume and value, protecting PHI and ePHI has never been more critical—or more complex. In this session, we’ll explore how AI is transforming cybersecurity in healthcare, with advanced monitoring, anomaly detection, and adaptive defenses tailored for compliance-heavy environments like HIPAA. Learn how techniques like UEBA, unsupervised learning, and AI-driven threat detection are being used to detect insider threats, stop credential misuse, and build resilient, compliant frameworks for modern healthcare systems. If you’re working at the intersection of healthcare, AI, and data protection—this session is for you.

Future Ready Web

How AI is becoming a true collaborator in development, why performance and composable architectures now define modern builds, and how design is shifting toward more organic, minimal, and human‑focused experiences.

Whether you’re a developer, designer, digital strategist, or simply tech curious, you’ll walk away with practical insights to apply to your next project—and connect with fellow tech leaders across Pinellas and Tampa Bay.

GRC on Agentic Workflows

AI agents don't just respond — they decide, act, and execute. Autonomously. And most organisations have no idea what their agents are doing, on whose behalf, or whether they could explain a single decision within 24 hours.
This session delivers a practitioner-grade framework for Governance, Risk, and Compliance in agentic AI environments. Attendees will learn how to inventory deployed agents, implement least-privilege architectures, enforce policy-as-code, and build the observability infrastructure that regulators, auditors, and courts increasingly demand.
With real-world case studies — Air Canada, Samsung, Microsoft Copilot — this is a candid briefing for CISOs and CIOs who govern AI at scale.

Agentic AI is operational in your enterprise. The question is whether it is controlled. This session examines the three pillars — Governance, Risk, and Compliance — through the lens of autonomous AI systems that browse, transact, and execute without step-by-step human approval. Delegates leave with a concrete 90-day roadmap, a GRC maturity model, and eight implementable improvement levers mapped to the EU AI Act, GDPR, SOC 2, and sector-specific frameworks. If you cannot reconstruct and defend a specific AI decision within 24 hours, this session is for you. Practical, evidence-based, and built for security and technology leadership.

Explainable AI agents for real-time data pipeline debugging

Delivered a technical session at IEEE SoutheastCon 2026, focusing on Explainable AI agents for real-time data pipeline debugging, emphasizing transparency, traceability, and enterprise AI reliability.

Delivered a technical session at IEEE SoutheastCon 2026, focusing on Explainable AI agents for real-time data pipeline debugging, emphasizing transparency, traceability, and enterprise AI reliability.

AI Copilot for Developers(Enyterprise Coding)

Invited speaker at the Global Skill Development Council (GSDC), where I delivered a technical session on “AI Copilot for Developers (Enterprise Coding)” to a global audience of software engineers and technology professionals. The session focused on enterprise-scale adoption of AI-assisted development using tools such as GitHub Copilot, emphasizing secure coding practices, productivity acceleration, and integration into CI/CD pipelines.

This engagement demonstrates recognized expertise in enterprise AI systems and developer productivity, contributing to the advancement of AI-driven software engineering practices. The talk addressed real-world implementation strategies, governance considerations, and measurable impact on software delivery efficiency, aligning with industry demand for responsible and scalable AI adoption.

enterprise AI adoption strategies

Featured speaker at Eminesphere Conference, discussing enterprise AI adoption strategies, including multi-model orchestration, production guardrails, and scalable AI systems.