Inspiration

With the rapid increase in digital scams across India, identifying fraudulent digital artifacts has become incredibly difficult for the average person. We were inspired to build a centralized, accessible tool to combat the rise of fake UPI payment receipts, deepfake media, and forged documents that cost people their hard-earned money and trust.

What it does

Satya-Kavach is an AI-powered digital forensics platform that acts as a comprehensive security shield. It features:

UPI Screenshot Inspector: Detects tampered amounts and fake app generator receipts.
Deepfake Inspector: Analyzes media to identify synthetic alterations and AI-generated content.
Document Forensics: Validates official documents to spot manipulation.

How we built it

We built the frontend and core framework using Next.js. For the heavy lifting in forensic analysis and OCR, we integrated Google's Gemini models via the @google/genai SDK. The entire application is deployed on Vercel for fast, edge-network performance, with version control managed collaboratively through GitHub.

Challenges we ran into

One of our biggest hurdles was managing production deployments during the final stretch. We encountered module resolution errors with our AI packages and Git desync issues that blocked our UI updates from going live. We resolved this by overriding the Vercel build cache and setting up a direct CLI deployment pipeline to force the latest UI changes to production.

Accomplishments that we're proud of

We are incredibly proud of taking a complex technical concept like digital forensics and packaging it into a clean, user-friendly interface with a fully functional dark theme. Getting the real-time AI analysis working seamlessly on the live Vercel link was a major victory.

What we learned

We gained deep hands-on experience with Next.js deployment environments, resolving Git conflicts in a team setting, and integrating powerful AI models into a web application to solve real-world security problems