I need an end-to-end AI marketing platform built specifically for law firms, from first database table right through to production deployment. The heart of the system will be machine-learning optimisation that continually improves campaign performance, lead scoring and overall client engagement for attorneys. Born out of a simple but powerful frustration: Businesses are drowning in disjointed, inconsistent communication. After years of helping companies shape their brand voice manually, we saw a smarter way. Whether you're scaling rapidly, managing multiple teams or brands, or just tired of rewriting the same onboarding doc for the 12th time, we exist for you. At minimum the build has to cover: • Core web application (front-end and secure back-end) • Modular ML pipeline that ingests campaign data, trains models and deploys updated recommendations automatically • Clean, lawyer-friendly interface that lets non-technical staff launch, pause and tweak campaigns in minutes I am open to layering in additional modules such as automated email campaigns, an analytics dashboard or even a chatbot assistant, provided they plug into the same ML backbone without bloating the codebase. Feel free to suggest alternatives if you have a better architectural approach. Tech stack is flexible as long as you choose tools proven for production-grade AI apps (e.g., Python, FastAPI, Node, React, TensorFlow/PyTorch, PostgreSQL). Code needs to be well-documented and checked into a private Git repository with clear setup instructions so my in-house team can continue iterating after hand-off. Acceptance criteria: 1. The platform trains and deploys ML models on real or sample legal-marketing data and surfaces actionable recommendations. 2. A user with no coding background can create, monitor and optimise a campaign end to end from the UI. 3. All critical paths are covered by automated tests and the app runs behind HTTPS on a cloud instance of our choice. If you can deliver clean code, transparent dev milestones and a working demo that meets the above, let’s get started.