# Introduction PredictRAM utilizes the combined power of computer intelligence (AI, ML) human intelligence(CI), and advanced technology to mitigate risk. It combines our sophisticated risk analytics and highly scalable processing capabilities to enable you to see the whole portfolio, understand risks and exposures and act with speed and precision. As a recognized FinTech Startup by DPIIT(Govt of India) and a proud member of the FICCI Startup program. The Startup Incubation and Innovation Centre, SIIC IIT Kanpur, incubates PredictRAM. We developed a Risk Management Network to predict & analyze financial and economic events with the help of data analytics AI, and ML models and it creates event-specific customized ETFs. Investors can hedge portfolios before any upcoming economic event to reduce portfolios’ systematic risk. By sourcing estimates from a diverse community of registered advisors, individuals, and different data points, we provide data that is not only more precise but is also a more representative view of expectations when compared to sell-side-only data sets which suffer from demonstrable biases. Our goal at PredictRAM is to give the market a transparent data set of accurate expectations while providing analysts with a platform to build a verifiable track record and mitigate portfolio risk against any financial and economic event. Many financial market aspirants, Students, and financial analysts, data scientists contribute to PredictRAM, resulting in coverage of over 200 stocks fundamentals and 25 economic indicators each quarter. --- # Agent Instructions: 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: ``` GET https://predictram.gitbook.io/docs/introduction.md?ask= ``` The question should be specific, self-contained, and written in natural language. 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.