Welcome to DeepXL
DeepXL is a forensic AI platform that detects manipulated documents, verifies identities, and extracts structured data — built for lenders, insurers, and government. Integrate via a simple API to catch AI-generated fraud that legacy systems miss.Our Models
Document Model
Detects AI-generated or altered documents and IDs — bank statements, invoices, passports, driver licenses, and more.
Object Model
Detects whether an image has been AI-generated or manipulated — photos, claim evidence, receipts, and other visual content.
Parsing Model
Extracts and parses structured data from IDs and documents — names, dates, addresses, amounts, and more.
ID-Selfie Model
Verifies identity by matching an ID document against a selfie image or video.
Model Details
Document Model
Detects AI-generated, digitally altered, or tampered documents — including bank statements, pay stubs, invoices, passports, and driver licenses. What it analyzes:- Pixel-level manipulation artifacts and metadata inconsistencies
- Font, layout, and formatting anomalies inconsistent with the issuing source
- Signs of generative AI fabrication (synthetic documents with no original)
Object Model
Detects whether a photo or visual asset has been AI-generated or manipulated — covering claim evidence photos, product images, receipts, and general visual content. What it analyzes:- GAN/diffusion model generation signatures
- Image splicing, cloning, and compositing artifacts
- Lighting, shadow, and perspective inconsistencies
Parsing Model
Extracts and normalizes structured data from identity documents and financial records — eliminating the need for manual data entry or custom OCR pipelines. What it analyzes:- Identity documents (driver licenses, state IDs, passports, Social Security cards)
- Financial records (bank statements, pay stubs)
- Extracts fields such as names, dates, amounts, account numbers, and document numbers
ID-Selfie Model
Verifies that a person presenting an ID document is the same individual captured in a selfie image or short video — combining liveness detection with facial matching. What it analyzes:- Biometric similarity between the ID photo and the selfie or video frame
- Liveness signals to prevent spoofing (printed photos, screen replays, deepfakes)
- Facial landmark detection and bounding box coordinates for both inputs
How It Works
- Authenticate with an API key or Bearer token
- Upload a document or image to an analysis endpoint
- Receive structured results with fraud scores, quality classifications, and detailed reasoning
- Retrieve associated files (originals, heatmaps) via the file retrieval endpoint
Supported File Types
| Format | Document Model | Object Model | Parsing Model | ID-Selfie Model |
|---|---|---|---|---|
| JPEG / JPG | Yes | Yes | Yes | Yes |
| PNG | Yes | Yes | Yes | Yes |
| WebP | Yes | Yes | Yes | Yes |
| Yes | No | Yes | No | |
| MP4 / Video | No | No | No | Yes |
Next Steps
Quickstart
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Authentication
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