From Financial Therapist to Infrastructure Builder:
Encoding a Decade of Regulatory Instinct into Code.
The Philosophy
My internal motivation has always been meaningful service. For over a decade, I functioned as a “Financial Therapist,” making an impact one family at a time by distilling complex regulatory concepts into confident, life-altering actions.
However, I realized that manual advocacy has a ceiling. I founded Quantum Dossier because I see the technology of today as the only way to scale that impact beyond what I could ever accomplish as one person. I am moving from helping individuals navigate the system to building the infrastructure that makes the system safer for everyone.
The Journey
I have operated at the intersection of high-stakes regulation and human vulnerability for my entire career. From preparing thousands of tax returns to navigating FINRA Regulation Best Interest (Reg BI) as a licensed representative (Series 6, 63, SIE), I saw exactly where the legal landmines are.
Crisis Management: During the 2020 economic shutdowns, I didn’t just file forms; I reverse-engineered federal guidelines to rescue family businesses and stabilize 42 self-employed clients through novel crisis filings.
Community Trust: I grew a book of business to 300+ clients by deeply embedding knowledge into community networks, proving that education is the most powerful form of sales.
The Pivot to Infrastructure
I am now translating that domain expertise into code. As AI moves toward “Agentic” workflows, it lacks the regulatory instinct I honed over 11 years.
I have spent the last year immersing myself in the cybersecurity community and studying the mechanics of Human-AI Collaboration. Combining this with nearly a decade of personal contribution to AI model feedback loops (RLHF)—including thousands of prompts rated on Grok and other frontier models—I am building the bridge that allows AI to offer the same safety and nuance I provided to my clients, at enterprise scale.
Strategic Focus
Translating Policy into Logic: Encoding the nuance of tax law and Reg BI into deterministic guardrails that LLMs cannot ignore.
Architecting for Trust: Designing the “Secure by Design” middle layer that allows enterprises to deploy agentic AI without compromising user safety or compliance.
