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Nyaya Setu – Intelligent Legal Complaint & Case Management Platform
Designed and developed a full-stack complaint and case management platform that digitizes the complete complaint lifecycle—from citizen reporting and evidence submission to verification, case assignment, investigation, and resolution. Implemented role-based access control and dedicated dashboards for citizens, authorities, police officials, and administrators. Built database-driven workflows for case tracking, evidence management, status updates, and centralized administrative monitoring.
nice work @Ishika Pradhan 😊
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💧 AQUAÉRA India — Premium Water Purification, Reimagined
Designed & developed a modern UI/UX-focused website for AQUAÉRA India, a premium water purification brand serving residential, corporate, and hospitality sectors.
The goal was to create a digital experience that feels clean, premium, and trustworthy while making product discovery and lead generation simple.
✨ Key Highlights
• Clean, premium light-theme design
• Mobile-first responsive experience
• Dedicated solutions for Home, Office & Hotel
• Smart product selection & lead capture
• One-tap WhatsApp & calling
• Consistent typography and visual design system
• Fast-loading, zero-bloat architecture
🛠️ Technology & Build
Frontend: HTML5 · Semantic HTML · Modern CSS3 · CSS Grid · Flexbox
Interactions: Vanilla JavaScript (ES6+) · Dynamic Form Logic · Smooth UI Interactions
Design System: Plus Jakarta Sans · Inter · CSS Custom Properties · Responsive Design
Performance: Zero-Bloat Architecture · Optimized Assets · Mobile-First Performance
Deployment: Vercel Edge Network · Zero-Config Static Architecture
🔗 Live Demo: https://aqua-ra.vercel.app/
💻 GitHub: https://github.com/HimanshuGehlot18/AQUA-RA-
The result: a fast, polished, conversion-focused experience built around simplicity, performance, and trust.
Clean design. Fast experience. Better conversions. 💧
The smart product selector is the part I'd test first. I'd show why it recommends a model for a home, office, or hotel, so the buyer reaches the lead form knowing what they are asking about.
just shipped the core of Skillship — an AI-powered LMS built for schools.
One platform, many schools, and one rule that shaped every decision: School A must never see School B's data. Tenant-scoped models, filtered querysets at the base class, UUIDs everywhere.
Four AI features live:
— Career Pilot: personalised career paths for students
— Question generator: chapter PDF in, board-aligned MCQs out
— Adaptive quizzes: difficulty follows actual performance
— Semantic search: teachers ask in plain English, pgvector finds the material
Django + DRF for the LMS core, a separate FastAPI service for all AI work (Gemini + a pgvector RAG pipeline), Next.js 14 on the front. Django brokers every AI call — the AI layer never touches the browser.
The hard part wasn't the AI. It was making multi-tenancy boring enough that no future dev can leak a school's data by accident.
Open for new work — full-stack builds, AI integrations, RAG pipelines, multi-tenant SaaS. Send me a project.
The tenant boundary is where I'd put the first failure test. I'd try to make a user from one school retrieve another school's record before I trusted any of the AI features.
I built ProofFace a visual provenance & content verification engine in Rust
I have been building ProofFace an end-to-end visual provenance and content verification engine built in Rust.
The idea is simple:
Finding an image online doesn’t prove that it’s authentic, original, or unchanged.
So I built a verification pipeline that goes from:
📸 Image input
→ 🧠 Neural face detection
→ 🔎 Web visual discovery
→ 🧬 Biometric similarity
→ 🔐 Deterministic SHA-256 fingerprinting
→ ⛓️ Polygon Amoy blockchain proof
→ ✅ Verification result
Some of the things I worked on:
• ONNX-based face detection
• 128-dimensional biometric embeddings
• Presentation attack detection
• Parallel visual candidate evaluation
• Cosine similarity matching
• RFC 8785 JSON canonicalization
• SHA-256 content fingerprinting
• Polygon smart-contract integration
• Automated unit & integration testing
The project currently has 30 passing tests.
What I enjoyed most was bringing several different areas together computer vision, Rust systems programming, cryptography, and blockchain into one reproducible verification workflow.
Would love to hear what you’d improve or add to a system like this.
