Side-by-side comparison of AI visibility scores, market position, and capabilities
User research repository and AI insights platform for research teams. Remote-first, raised $4M+, helps teams organize and surface research findings.
Aurelius is a user research repository and insights platform designed to help UX researchers, product designers, and product managers organize, tag, analyze, and share research findings across an organization, transforming scattered interview notes, survey results, and usability test data into a searchable institutional knowledge base that can inform product and design decisions. Founded in 2016 as a remote-first company, Aurelius has raised more than $4 million and serves product and research teams at technology companies that run continuous discovery programs and struggle to prevent research from being siloed in individual researchers' files or forgotten after a project concludes.\n\nAurelius's platform provides a structured workspace for uploading and organizing research artifacts — interview transcripts, notes, survey responses, and reports — tagging observations with themes and categories, and synthesizing tagged observations into insights and recommendations. The search capability allows any team member to retrieve relevant past research on a topic, reducing duplicate research and enabling evidence-based product decisions even when the original researcher has left the team. AI features assist with transcript analysis, automatic tagging suggestions, and insight generation from tagged observations.\n\nAurelius competes with Dovetail, EnjoyHQ, and Condens in the research repository and insights platform market. Its focus on insight synthesis — moving beyond storage to helping researchers generate and share actionable findings — differentiates it from simple file repositories, while its lightweight pricing and ease of setup make it accessible to smaller research teams that cannot justify enterprise research platforms. The company positions itself as the system of record for product research knowledge within organizations that take continuous discovery seriously.
a2z Radiology AI raised $20M in 2025 for its whole-body AI that simultaneously screens for 24+ conditions across CT scans — from incidental cancers to cardiovascular risk — in a single automated read.
a2z Radiology AI has developed a whole-body CT analysis platform that simultaneously screens for over 24 medical conditions across a single CT scan, including incidental cancers, coronary artery disease, aortic aneurysm, bone density loss, and organ abnormalities. The AI acts as a second reader that radiologists can use to catch incidental findings that fall outside the primary reason for a scan — a major source of missed diagnoses.
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