> 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/market-landscape/case-study-existing-platforms.md).

# Case Study: Existing Platforms

Current leading prediction platforms already demonstrate **strong market traction and profitability**, validating the viability of this sector.

Representative metrics include:

* **Total Value Locked (TVL):** $433M+
* **30-Day Trading Volume:** $4.59B
* **Profit Margins:** \~70%

These figures indicate that prediction markets are not only growing, but are also capable of generating **sustainable revenue and strong cash flow models**.

From these results, several conclusions can be drawn:

* There is **significant user demand** for prediction-based trading systems
* The market supports **high-margin business models**, particularly when liquidity is sufficient
* Trading-based mechanisms outperform purely outcome-based systems in scalability

CubiC builds on this foundation by introducing **AI-driven liquidity provision and execution efficiency**, addressing limitations in speed, depth, and capital utilization seen in existing platforms.