Jua

Jua is a physical AI platform built around the EPT-2 foundation world model, which learns from dense physical data to simulate the atmosphere and other real-world systems. Its Athena agent uses these simulations to make optimized decisions for applications like weather and energy forecasting.

Jua is designed for energy traders, utilities and grid operators, weather-dependent industries, enterprise data science teams, AI and ML engineers, quantitative trading desks, and climate or atmospheric researchers who need accurate physical predictions and decision support.

Jua helps organizations turn complex physical reality into programmable workflows, improving forecast accuracy, risk management, and operational decisions in domains where small errors can be very costly, such as energy markets and grid operations.

Yes, Jua provides API access so teams can integrate its world model outputs and agent decisions directly into existing systems, dashboards, and automated workflows.

Unlike traditional approaches, Jua uses a foundation model trained on dense, multi-source physical data combined with an intelligent agent layer, enabling both high-fidelity forecasts and automated decision-making tailored to specific operational objectives.

Yes, Jua is designed for production use across utilities, trading desks, and other industries that depend on accurate, global, and high-frequency physical predictions for day-to-day operations.

Specific pricing details are not publicly listed and likely depend on enterprise scope or usage. Organizations should contact Jua directly to discuss pricing and deployment options.