> For the complete documentation index, see [llms.txt](https://docs.yala.org/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.yala.org/prediction-market-intelligence/introduction.md).
# Introduction
### What Is Yala 2.0?
Yala 2.0 is an AI-native fair-value agent system for global prediction markets.
The system is designed to:
* Generate probability estimates for future outcomes
* Act as a fair-value reference for prediction markets
* Improve predictive accuracy and decision quality
* Make advanced probabilistic tools accessible to a broader set of users
Yala does not operate a prediction market. Instead, it produces fair-value probability signals that users, agents, and markets can use to evaluate prices and decisions.
### The Problem: Missing Fair Value in Prediction Markets
Prediction markets determine prices through order-book matching, where prices directly represent probabilities. While this mechanism efficiently aggregates information, it does not provide a systematic reference for true or fair probability.
As a result:
* Market prices may diverge from statistically grounded probabilities
* Information asymmetry favors sophisticated participants
* Mispricing can persist during high-uncertainty events
Comparable financial markets, such as options markets, rely on formal fair-value models (e.g., Black–Scholes) for pricing and risk management. Prediction markets currently lack an equivalent framework.
Yala is designed to fill this gap by acting as a fair-value intelligence source for prediction markets.
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