CaseScan

CaseScan is a specialized detection layer designed to catch child sexual abuse material (CSAM) that other moderation tools might miss. It doesn't replace your current moderation stack — it sits alongside it, scanning images and videos as they're uploaded to your platform. The tool combines perceptual hashing with AI-powered visual analysis to identify known CSAM, altered versions of known files, newly created content, and even AI-generated CSAM. It's built for platforms where user-generated content flows in at scale: social media, cloud storage, file-sharing services, and enterprise communities.

How does it work? Content enters via API or SDK at the point of upload, whether that's a direct file upload, a stream, an avatar image, or a chat attachment. CaseScan's AI models and hashing algorithms analyze the media in real time, then produce a risk score, a recommended action, and a structured evidence file that can feed directly into blocking, human review, escalation, or takedown workflows. The company emphasizes that hash matching alone is not enough — many CSAM files are altered or newly generated, so the AI component is central to catching what hasn't been seen before. The tool also supports side-by-side evaluations: you can run CaseScan alongside your existing provider to compare detection coverage, speed, and false-positive rates using your own content and policies.

Who is this for? Trust and safety teams at user-generated content platforms, cloud storage providers, and large online communities. If your platform handles image and video uploads at scale and you're worried about CSAM slipping through a general-purpose moderation suite, CaseScan offers a dedicated layer focused solely on this high-risk category. It's also useful for organizations that want to benchmark their current detection — the controlled evaluation feature lets you measure exactly what your existing workflow is missing before an incident happens.