Aurora AI Intelligence
Scientists are asking AI increasingly specific questions about scientific challenges, technologies and suppliers. Aurora helps life-science companies examine the sources AI cites, understand market-level patterns and evaluate their own visibility across the scientific buying journey.
AI visibility is not a single ranking or a single moment. The information sources represented in AI-generated responses can differ by scientific question, life-science market and stage of supplier evaluation. Understanding those differences can help marketing and commercial teams identify what to investigate, where evidence or content gaps may exist, and how to prioritize further analysis.
Start with the industry landscape, examine the markets that matter to you, then understand how your company compares with competitors.
Question answered: What source patterns emerge across life science?
Question answered: What sources does AI cite in the markets I care about?
Question answered: How does my company appear relative to competitors across buying-journey questions?
Related diagnostic service
Understand how your website and scientific content support AI discoverability. Aurora assesses content structure, accessibility, evidence presentation and other relevant factors, then identifies practical opportunities for improvement.
The audit evaluates readiness and opportunities; it does not promise placement or citations in AI answers.
Aurora’s source-intelligence research is designed around scientific markets and five researcher-defined buying-journey question stages. Our analysis classifies cited sources by type, examines supplier-owned content in greater detail, and resolves available DOI information to understand the scientific literature represented in AI responses. The result is descriptive evidence about AI-cited sources—not a claim about scientists’ actual purchases or what causes AI systems to recommend a supplier.
Source records are citation occurrences across AI responses, not 27,219 unique URLs. The classified-share analysis uses 26,513 classified citation records after exclusions and unresolved classifications.
Featured research
Explore selected findings from Aurora’s analysis of the sources AI cites across the life-science buying journey—including shifts between scientific publisher sources and supplier-owned content, differences in supplier content types, and variations across markets.
Tell us which life-science markets, suppliers or competitive questions matter most. We’ll help identify the right research or diagnostic approach.
