Mini-project architecture
From frontend screening to a Python verification system
This working Vite/React frontend is the presentation and interaction layer. A production implementation should place sensitive OCR, forensic models, institution matching, and audit logic in a secure Python API.
Implemented in this frontend
Usable now in the browser.
- Responsive multi-page interface
- Accessible upload and form validation
- PDF/JPG/PNG checks up to 10 MB
- Real SHA-256 file hashing
- Local duplicate-file detection
- Rule-based risk explanations
- Searchable local record history
- JSON report export and deletion
Requires a Python backend
Not claimed as active in this build.
- OCR and layout understanding
- Pixel-level edit and splice detection
- AI-generated image/text classifiers
- Signature or seal comparison
- Authorized issuer database queries
- Encrypted server-side evidence storage
- Human-review and audit workflow
Recommended system workflow
A defensible verification result uses several layers rather than one AI score.
Document intake
Accept PDF or image files with claimed holder, number, type, issuer, and signature information.
Pre-processing
A future Python service can run OCR, normalize images, inspect PDF objects, and extract document structure.
Forensic analysis
Combine tamper localization, signature comparison, AI-image detection, typography checks, and duplicate hashing.
Authority verification
Connect only to approved institution, school, bank, tax, or identity verification providers with consent.
Decision report
Return explainable checks, confidence, risk indicators, and a manual-review path instead of an unsupported claim.
Responsible verification principles
Do not overclaim
A model can flag risk, but “genuine” should require authority confirmation or verifiable cryptographic evidence.
Protect sensitive identity data
Aadhaar, PAN, school, and bank records need consent, masking, encryption, access controls, and a deletion policy.
Keep a human in the loop
High-impact decisions should expose evidence and support manual review, correction, and appeal.