TruthLens

AI-powered deepfake detection for trusted digital media verification.
Explore multiple AI detectors for images, videos, and voice deepfakes.
Monitor scans, analytics, and authenticity reports in real time.
Review previous scans and track suspicious media activity.
Upload media and start instant deepfake detection analysis.
Drag, drop, and securely upload supported media files.
View authenticity scores and detected manipulation indicators instantly.
Customize preferences, notifications, and account security options.

Inspiration

The rise of AI-generated deepfakes and voice cloning has made digital media harder to trust. From scam calls to fake videos and identity fraud, we wanted to create a platform that helps people instantly verify whether media content is real or manipulated using AI.

What it does

TruthLens is an AI-powered deepfake detection platform that analyzes images, videos, and audio files for signs of AI manipulation. Users can upload media and receive an authenticity score, risk analysis, and detected manipulation indicators through an intuitive dashboard.

How we built it

We built the frontend using Next.js and Tailwind CSS for a modern responsive interface, while the backend was developed with Python and FastAPI. AI detection models were integrated using PyTorch and pretrained models from Hugging Face to analyze visual and audio inconsistencies in uploaded media.

Challenges we ran into

One of the biggest challenges was balancing detection accuracy with performance, especially for larger video files. We also faced difficulties in handling multiple media formats, improving real-time analysis speed, and designing results that are understandable for non-technical users.

Accomplishments that we're proud of

We successfully created a functional prototype capable of analyzing media uploads and generating authenticity reports with a sleek cybersecurity-inspired interface. We are especially proud of the clean user experience, real-time scan workflow, and scalable architecture for future AI integrations.

What we learned

Through building TruthLens, we learned how AI models detect synthetic media artifacts, how to process multimedia data efficiently, and how important explainable AI is in cybersecurity applications. We also improved our skills in full-stack development, API integration, and AI workflow deployment.

What's next for TruthLens

We plan to add live deepfake detection for video calls, browser extensions for instant media verification, and enterprise-grade APIs for fraud prevention systems. Future versions will also include blockchain-based media provenance tracking and advanced AI watermark detection.