> For the complete documentation index, see [llms.txt](https://cubic-2.gitbook.io/cubic-docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://cubic-2.gitbook.io/cubic-docs/introduction/what-is-cubic.md).

# What is CubiC?

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CubiC is an **AI Agent–driven predictive liquidity network** that redefines how prediction markets function by transforming user insights into **real, executable trading activity**. Rather than treating predictions as isolated bets or opinions, CubiC integrates them directly into a **quantitative trading framework**, where every prediction can influence market behavior and generate measurable financial outcomes.

At its core, CubiC bridges the gap between **human intelligence and automated financial systems**. Users contribute predictive signals based on real-world events, while AI Agents interpret, price, and execute these signals within a high-performance trading environment. This creates a system where information is continuously processed, optimized, and converted into trading strategies.

The platform is built on four foundational pillars:

* **Prediction Behavior** – Users participate by forecasting outcomes across various domains such as macro events, crypto markets, technology trends, and sports. These predictions act as raw market signals.
* **AI-Driven Execution** – AI Agents analyze prediction data, apply probabilistic models, and execute trades automatically without requiring manual intervention.
* **High-Performance Trade Matching** – A robust trading infrastructure ensures fast, efficient order matching and real-time liquidity management.
* **Automated Profit Distribution** – Profits generated from trading activities are distributed systematically, enabling users to benefit from continuous market participation.

Together, these components form a **closed-loop predictive trading ecosystem**, where:

* Predictions generate signals
* Signals trigger AI-driven trades
* Trades produce real market returns
* Returns are redistributed into the system

This loop allows CubiC to evolve dynamically, improving efficiency, liquidity, and profitability over time while aligning the interests of users, AI systems, and the broader market.