Applied AI systems for prediction, analysis, automation and decision-making.
Solve difficult problems using AI, quantitative modeling and intelligent systems.
Explore Solutions →Simulators and platforms we build and operate ourselves — some free, some paid.
Explore Software →We combine these fronts as each problem requires — never selling technology the project doesn't need.
Predictive modeling, forecasting, anomaly detection, classification and optimization — built for production, not just notebooks.
RAG systems, enterprise knowledge assistants, AI agents and LLM integration designed around real workflows.
Data pipelines, analytics, dashboards and time-series analysis that turn raw data into a decision layer.
Scientific machine learning, computational modeling and simulation for complex and nonlinear systems.
A gamified investment simulator for learning how the Brazilian stock market really works — real market data, a portfolio to manage and instant feedback, with no real money at risk.
A gamified investment simulator for learning how the Brazilian stock market really works — real market data, a portfolio to manage and instant feedback, with no real money at risk.
Practical software for analysis, simulation and better decisions — free to use.
Growth mode projects your wealth forward; Goal mode solves backward for the contribution, time, or return a target actually requires.
Open calculator →Model accumulation, fixed income, equities, inflation and withdrawals together — with Monte Carlo uncertainty and FGC coverage checks.
Plan your retirement →Fixed-income comparisons and loan amortization are next.
A sample of what we've already built, with the method behind each solution.
Projects are structured around the problem, the available data, the target metric and the expected outcome — not a fixed methodology template.
AI that informs real decisions has to hold up under scrutiny — not just look good in a demo.
Paulo founded Prota AI with his experience in computational physics and data science, backed by peer-reviewed publications on neural network synchronization, critical transitions, and complex systems. That background shapes how the company works: problems are approached with the same rigor as scientific research, not wired together from generative AI APIs alone.
Let's assess, with technical rigor, whether AI can actually solve it — and how.