A scoped, project-based engagement to design, train, and deliver a working machine learning model prototype. Built by a published ML researcher (IEEE-BIBM graph neural network paper, Yale computational biology research). Ideal for founders, labs, or small teams that need a functional model fast without hiring a full-time ML engineer. Includes: scoping call, working prototype + code, documentation, one revision round, and a final walkthrough call.