I want to move an idea from concept to a working AI prototype and need an experienced developer to lead the way. At this stage I’m deciding whether the system should focus on data analysis, process automation, or a richer user experience, and I’m open to the most suitable technology—be it classic machine-learning pipelines, natural-language processing, or computer-vision techniques. My company operates across healthcare, finance, and e-commerce, so adaptability and clean abstraction are essential. You’ll start with a short discovery call to refine goals, data requirements, and success metrics, then design and implement a modular solution. Python is my default preference for its rich AI ecosystem, but I’m happy to consider another stack if you explain its benefits. Whichever path we choose, I expect transparent algorithm choices, readable and well-commented code, and straightforward deployment (Docker, virtualenv, or similar). Deliverables • Architecture & tech-stack document • Working prototype in a private Git repo with setup instructions • Demo (screen recording or live session) showcasing performance on an agreed dataset • Knowledge-transfer session and final report Acceptance criteria: the model meets the performance benchmarks we set together, unit tests pass, and the deployment script reproduces results in a fresh environment. When you respond, outline the first approach you’d take, relevant tools or frameworks, and a concise timeline.