I use data-driven decision making to redesign workflows and identify where AI can create value.
I turn those ideas into working prototypes that show how data, prediction, and human judgment can improve business decisions before anything scales.
A business leader trained in AI and international business through my MBA at Arizona State University, shaped by professional experience in operations and consulting.
Featured projects
Workflow Assessment Tool
Live or simulated
A narrow, schema-constrained model call can turn a vague process description into a structured, decision-ready breakdown.
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Market Expansion Prioritizer
Deterministic, synthetic data
AI predictions are rarely certain. Weighting them by what matters most to the business turns a forecast into a ranked, defensible decision.
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Customer Escalation Triage
Live or simulated
Confidence and the cost of being wrong, not the severity label alone, should decide how much of a decision gets automated.
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Data as Fuel for AI
Client-side, browser-trained
A model's output quality is bounded by how much data and training time actually went into it, not by how confident it looks.
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Model Drift Monitor
Deterministic, synthetic data
A model that worked at launch can quietly become unreliable as its environment changes, and when to retrain is a business decision, not a technical afterthought.
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Visual Quality Control
Deterministic, synthetic data
Perceiving a defect and deciding what to do about it are two different steps, and quality standards and inspection cost, not the image alone, set where the line between them sits.
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Adaptive Personalization with AI
Interactive replica
The click, store, rank, adapt loop that powers AI personalization at scale, made visible in miniature.
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