I have an AI-driven idea that needs to be shaped into a working product. At this stage the high-level concept is clear, but the specific objective, data sources, and target industry still need to be defined through discovery and rapid prototyping. I want to collaborate with someone who can guide the scoping process, recommend suitable machine-learning approaches, and then build a small proof-of-concept that demonstrates real value. The engagement will begin with a short requirements workshop and data audit, move into algorithm selection and iterative model training (Python, scikit-learn, TensorFlow or similar), and end with a lightweight demo that I can show to internal stakeholders. Clear documentation and well-commented code are essential because they will form the basis for a later production rollout. Deliverables • A concise discovery report summarising use-case, data assumptions, and proposed ML workflow • Reproducible notebook or script that ingests sample data, trains the model, and outputs performance metrics • Brief deployment outline highlighting next steps for scaling Acceptance criteria • Discovery report approved by me before coding starts • Proof-of-concept reaches the agreed evaluation metric (to be finalised together, e.g., ≥85 % accuracy or equivalent) • All code runs end-to-end on my machine with clear setup instructions If this sounds like the right challenge, I’m ready to get started and iterate quickly.