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Review documents, identity files, and images for signs of manipulation

DeepXL analyzes submitted documents and images for signs of manipulation. Its products cover financial records such as paystubs and invoices, identity documents, and photographs used as evidence in insurance claims. The platform examines file structure, origins, and consistency, then presents risk classifications with supporting findings.
Reviewers can inspect confidence scores, visual heatmaps, and explanations when deciding which submissions need closer attention. Data extraction can help populate application fields, while duplicate and reused-content checks add context across submissions. DeepXL offers an API and a sandbox for integrating the analysis into existing processes. It is intended for lenders, insurers, and public-sector organizations reviewing documents at scale.
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