I view code as the most efficient tool for social architecture. My entry into computer science wasn’t driven by a classroom assignment, but by a survival mandated search for structure after experiencing domestic violence. In the wake of trauma, I discovered that while my physical environment was volatile, syntax was consistent. I didn’t just learn to program; I learned to build a logical foundation for a life that had been stripped of one. My self-taught proficiency in HTML, CSS, and JavaScript was the starting point for a deeper technical pursuit: leveraging Artificial Intelligence (AI) to solve resource allocation failures. I am pursuing software engineering with a focus on graduate-level AI research, specifically in the field of Algorithmic Equity. My goal is to develop machine learning models that account for thin data profiles. In many underserved communities, traditional data for financial vetting simply doesn't exist. I aim to build AI systems that can interpret alternative data points, such as community-based savings habits, to unlock institutional access for those who are currently invisible to standard algorithms. The qualitative data for my technical ambitions comes from my work as founder at Rego Foundation. What began as a safe-space club for survivors has scaled to reach over 8,000 young women across Uganda. As we grew, I saw exactly where manual, informal processes failed. This led me to develop RegoNow, a digital framework designed to formalize and secure the group-savings systems common in these communities. By digitizing these informal economies, I am creating the very datasets needed to eventually deploy AI-driven financial tools that accurately reflect the creditworthiness of marginalized entrepreneurs. For instance, in a traditional FinTech model, an algorithm might look at a woman in Uganda and see "no bank account, no credit history, low-income area" and assign a high-risk score. An Equity-driven AI, however, would be designed to recognize consistent weekly contributions to a community savings circle (RegoNow), 100% repayment rate within that circle and a growing micro-enterprise. My non-technical background gives me a ground-truth edge over other engineers. I do not build for a hypothetical user; I build for the women I sit with every week who require secure, low-latency tools to protect their capital and build sustainable, self-sufficient lives. I intend to establish a Technology and Innovation Center that operates as a hybrid incubator—a production house where young people use modern tech stacks to solve local logistical and financial bottlenecks. By combining AI research with localized fintech tools, I plan to create an ecosystem where technical skill leads directly to economic autonomy. A biased algorithm is a social failure, and a social problem is often a system awaiting a better architectural solution. I am not looking to join the tech industry to maintain the status quo; I am here to re-engineer the points of entry for those who have been systematically left offline.