The systems, automation, and decision work behind my approach to helping companies navigate AI and scale it across the enterprise.
Identity, platforms, and recovery: foundations for controlled AI adoption.
99.99%
uptime through the remote cutover
Moved a distributed workforce from Google Workspace to Microsoft 365 with secure endpoints, adoption playbooks, identity controls, and governed cutover.
25%
faster claims turnaround
Modernized healthcare operations with connected billing, reporting, workflows, and governance for a reliable clinical operating backbone built for adoption.
35%
faster onboarding in the first quarter
Unified payroll, benefits, finance, and workforce reporting in ADP Workforce Now with automation and shared data that teams could run confidently.
Connecting data and AI to the workflows teams already run.
200
teammates enabled across 10 departments
Connected finance, operations, and change data in Microsoft Fabric for workflow automation, adoption measurement, and executive decisions.
45%
fewer audit findings in the first quarter
Delivered privacy-aware AI coaching inside healthcare workflows to improve documentation quality, support clinical oversight, and make adoption measurable.
Reliable inputs and clear assumptions for business decisions.
Product engineering experience that keeps usability and reliability in view.
60%
longer average sessions after automation
Designed an offline-first mobile recipe and fermentation app for tracking, reminders, recipes, and community sharing when connectivity dropped.
>10k
requests per minute on edge APIs
Built a typed, reproducible finance platform that keeps calculations authoritative across dashboards, APIs, and MCP with explainable, audit-ready results.
Whether you are choosing a use case or scaling across teams, connect the AI ambition to the systems, people, and operating constraints behind it.