# FAQ **Q: How accurate are SAG3.ai's analyses?** \ A: SAG3.ai uses advanced AI models trained on vast amounts of cryptocurrency and blockchain data to provide objective analyses. While highly accurate, these should be used as one input among many for investment decisions. **Q: How often is data updated?** \ A: Research data is collected fresh for each analysis. For tracked projects, data is updated according to monitoring schedules. **Q: Can I analyze private or pre-launch projects?** \ A: SAG3.ai requires public information to perform analysis. Projects with limited public data may receive incomplete analyses. **Q: How are the attribute scores calculated?** \ A: Each attribute score is determined by our AI models evaluating specific criteria relevant to that attribute. The overall score is a weighted average of all attribute scores. **Q: What makes SAG3.ai different from other crypto analysis tools?** \ A: SAG3.ai combines deep AI-powered research with nuanced scoring across multiple attributes, plus automated social sharing capabilities - a comprehensive approach not found in other tools. **Q: How can project teams use SAG3.ai?** \ A: Project teams can gain objective insights into their strengths and weaknesses, competitive positioning, and community perception, helping guide development and marketing efforts. **Q: Can I export or share analysis results?** \ A: Yes, analysis results can be shared via direct links or through the automated social sharing features. **Q: How does the sentiment analysis work?** \ A: Our system collects and analyzes social media posts, community discussions, and market reactions to determine overall sentiment and identify key themes. --- # 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://docs.sag3.ai/more/faq.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.