Sentinel: AI Quality-Assurance Platform

Sentinel is a proof-of-concept system that evaluates creative media generated for brands, checking brand efficacy, brand alignment, and generation consistency. It serves as an additional validation step within Queen One's product stack, evaluating AI-generated images against established brand guidelines and providing a secondary quality signal.

The reason it exists: generative pipelines can produce beautiful images that are quietly wrong for the brand: off-palette, off-tone, or inconsistent from one generation to the next. A human can catch that, but not at pipeline speed. This platform gives the stack a machine-speed reviewer that flags inconsistencies, assesses output accuracy, and supports product refinement before a human ever has to look.

I designed and prototyped it with agentic workflows across Claude, Codex, Figma, and Antigravity, sitting between product strategy and technical development, translating the company's broader vision into practical concepts, testing processes, and product recommendations.

Through this project I strengthened my skills in product ideation, rapid prototyping, AI quality assurance, agentic workflow design, vibe coding, and cross-functional communication.