Side-by-side comparison of AI visibility scores, market position, and capabilities
YC W26 agentic video editor for growth teams. Generates first cuts from footage + goals in minutes using multimodal LLMs; runs in browser via WebGPU.
Cardboard is an AI-native video editing company that graduated from Y Combinator's Winter 2026 batch. The company was founded to eliminate the manual, time-intensive process of editing video content for growth and marketing teams. Its core technology applies multimodal large language models to understand raw video footage in the context of a team's goals, then autonomously generates a polished first cut — compressing what previously took hours into minutes.\n\nCardboard's platform runs entirely in the browser using WebGPU, removing the need for desktop software installation and enabling collaboration across teams without version conflicts. The agentic editor accepts footage alongside a creative brief or campaign goal, then makes sequencing, pacing, and cut decisions in line with that intent. This goal-aware editing approach is designed for performance marketing teams, social media managers, and growth hackers who produce high volumes of short-form content across platforms like TikTok, Instagram, and YouTube Shorts.\n\nAs a YC W26 company, Cardboard is in early-stage growth and is focused on building its customer base among digital marketing teams and agencies. The product addresses a significant bottleneck in content pipelines where video editing talent and turnaround time limit the volume and velocity of campaigns. By democratizing professional-quality editing through agentic AI, Cardboard positions itself to become essential infrastructure for high-output growth teams that treat video as a core performance channel.
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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