> For the complete documentation index, see [llms.txt](https://docs.awenetwork.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.awenetwork.ai/applications/polyvaults.md). # Polyvaults ### What agents do **Polyvaults turns prediction-market theses into AI-curated, vault-backed indexes.** Prediction markets contain thousands of individual outcomes. Expressing a broader view often requires finding related markets, selecting the correct positions and deciding how much weight to assign to each one. Polyvaults turns that process into a structured product. ### How it works Describe a thesis in natural language. Polyvaults screens live Polymarket markets, selects relevant YES or NO outcomes and proposes an index with suggested weights. The resulting index can be explored, tracked, shared, forked and—when available—deposited into through a vault-backed version. ### Product surfaces #### Custom Index Builder Create an index from a natural-language thesis. Polyvaults identifies relevant markets and proposes the positions and weights that best represent that view. #### Index Marketplace Discover public indexes, inspect their component markets and compare their paper performance. Existing indexes can be tracked, forked or accessed through vault-backed versions. ### From individual bets to structured views A single prediction market expresses a view on one outcome. A Thesis Index can express a wider idea across several related markets—for example, a political trend, a macroeconomic outlook or a sports tournament. This makes prediction-market exposure easier to construct, compare and monitor. ### Built on AWE Polyvaults is part of AWE’s application layer: a live product where agents can interpret market information and act on it. It demonstrates the demand side of the Agentic World Economy—using agent infrastructure inside real, adversarial markets. [Open Polyvaults →](https://app.polyvaults.ai/) [Read the Polyvaults documentation →](https://docs.polyvaults.ai/) --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://docs.awenetwork.ai/applications/polyvaults.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.