The technical architecture for this project involves a comprehensive setup designed for high-impact analytics and robust security features. The frontend and backend utilize Next.js 14+ with TypeScript and Tailwind CSS, creating a premium user interface meant for advanced analytical tasks. This is supported by a cleanly structured relational database in PostgreSQL, with compatibility for Supabase. The database includes dedicated enums, immutable triggers in plpgsql for internal audits, and extreme security through Row-Level Security (RLS) policies. Access control is managed via a Role-Based Access Control (RBAC) system, natively configured for key profiles in finance, human resources, and IT infrastructure. Artificial intelligence is a core component, with optimized endpoints integrated with the Gemini 1.5 Pro multimodal model. This AI framework is aimed at conducting financial analysis and automatically projecting Capex/Opex deviations, with outputs strictly formatted in JSON. The project’s infrastructure is designed for zero friction in portability and delivery, leveraging a fully Dockerized environment. It features a production-ready multi-stage setup and a docker-compose.yml file that facilitates running PostgreSQL 15 alpine and the web app simultaneously with a single command. Comprehensive documentation includes a detailed corporate README and a three-step technical deployment guide for Supabase and Vercel, ensuring an efficient setup process.