Tylo AI’s Research Assistant references a broad and meticulously curated collection of data sources to ensure its insights are accurate and reliable. These data sources collectively ensure that the tool provides well-rounded, evidence-based answers to a wide range of research questions.
The primary data sources include:
1. Academic Papers: The AI accesses over 100 million academic papers from reputable journals and research institutions worldwide. These papers cover various disciplines, providing a rich foundation for research inquiries.
2. Global Patents: Tylo AI references a comprehensive database of global patents, which is particularly valuable for innovation-related queries. This allows the AI to identify trends, emerging technologies, and novel inventions that are shaping various industries.
3. High-Credential Online Resources: The AI supplements its database with high-credibility online sources. These include resources indexed by platforms like Google Scholar, ensuring that the AI’s outputs are robust and up-to-date.
4. Internal Knowledge Graph: The AI also utilizes Quantumrun’s proprietary Knowledge Graph, which organizes and links information from various domains. This structured data helps the AI make connections between disparate pieces of information, enhancing the relevance and context of its answers.
5. Vector Database: The Vector database is another key component, storing data in a way that allows the AI to understand semantic relationships between different pieces of information. This enables the AI to deliver contextually accurate answers, even for complex or nuanced queries.
