Neural network grid abstract
Case Study — AI Identity Verification

VERITAS
STREAM

A multi-layered deep learning tool designed to identify and flag deepfakes in static images and live video streams with high accuracy. *Ongoing Project*

The Erosion of Digital Truth.

As generative AI rapidly advances, hyper-realistic deepfakes are becoming a severe threat to authentication systems, media integrity, and personal security. The challenge was building an application-level tool capable of scrutinizing media beyond the visual spectrum, catching pixel-level anomalies and metadata manipulation that the human eye misses.

Live-Stream Frame Analysis
Micro-Artifact Detection Layer
Abstract AI and face scanning

Multi-Vector Analysis.

psychology

CNN Artifact Detection

Deployed Convolutional Neural Networks (CNNs) trained specifically to identify the minute blending boundaries, edge mismatches, and temporal flickering common in AI-generated media.

data_check

Steganography Checks

Integrated deep-scan algorithms to detect hidden data payloads, structural anomalies, and steganographic manipulation within the media file headers.

manage_search

EXIF Metadata Audits

Automated parsing and validation of EXIF data, searching for compression footprints, software tags, or missing camera profiles indicative of synthetic generation.

Real-Time Verification.

Cloud Integrated
Data analytics UI dashboard
Camera lenses and optics
React code block on dark theme

The Stack.

A full-stack implementation connecting high-performance AI modeling with a responsive frontend.

TF TensorFlow
Py Computer Vision
React Frontend UI
cloud Cloud Backend
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