> For the complete documentation index, see [llms.txt](https://docs.alva.xyz/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.alva.xyz/welcome-to-alva.md). # Welcome to Alva Alva is your Quantamental Investing AI Agent. Designed to supercharge your investment process, Alva automates the entire research workflow – from initial idea generation and deep data analytics to real-time trend monitoring, robust strategy formation, and thorough backtesting. Built collaboratively with the investment community, for the community, we empower you to build, share, and grow your investment edge together.\ \ Alva leverages TradingView technology for showcasing price charts. > *TradingView, a sophisticated platform designed for traders and investors, is supported with technologies that can be accessed via web browsers, desktop software, and mobile applications. It provides users with real-time data, such as the* [*Dow Futures*](https://www.tradingview.com/symbols/CBOT_MINI-YM1!/) *and* [*BTC USD Chart*](https://www.tradingview.com/symbols/BTCUSD/)*, the latest financial news, in-depth financial reports, a Stock screener and an Economic calendar.* Alva is here to be your research sidekick, market pulse monitor, and conversation companion. Ask Alva anything, and let the interactive exploration begin. --- # 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 by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://docs.alva.xyz/welcome-to-alva.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. 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.