Large-scale check selection
We test candidate checks across broad data, compare their behavior, and filter out checks that are noisy, brittle, or not informative enough for operational use.
Research-led file fraud detection.
Essential-FD is built around research, measurement, and careful selection. We evaluate many protection checks over large datasets, then keep only the checks that prove robust, informative, and useful in real review workflows.
Researchers building the system
Our team is made up of researchers who work on file analysis, document forensics, AI-generated content, and practical fraud-detection workflows.
Academic and institute partners
We work in collaboration with the Fraunhofer Institute and research partners to keep our approach grounded in current technical research.