Building practical AI systems for document intelligence, legal research, automation, and secure software.
I am a B.Tech Computer Science student at Brainware University, working across AI engineering, backend development, application security, data analysis, and blockchain.
I believe in learning by doing: building systems, finding security flaws, optimizing backend operations, and turning experimental ideas into reliable, production-ready applications.
An all-in-one AI workspace designed to bring document analysis, grounded legal chat, research, and drafting into a single interface.
Key Development Areas:
- 🔍 Source-grounded AI conversations — anchoring AI answers to specific sections of uploaded documents.
- 📄 Large PDF processing & analysis — extracting structure and text from complex legal files.
- 🧠 Retrieval-Augmented Generation (RAG) — engineering prompt context and semantic search databases.
- 🔒 Document & conversation isolation — ensuring strict user-data boundaries and privacy.
- ⚡ Scalable background-processing pipelines — executing heavy tasks asynchronously.
- 💻 NotebookLM-inspired workspace design — designing custom interfaces for reading, research, and note-taking.
- 🛡️ Secure multi-user architecture — preventing cross-tenant data leaks and unauthorized access.
The goal is not just to create another chatbot, but to build a focused workspace where documents, research, reasoning, and drafting remain connected.
- 01. Improve RAG answer quality and citations
- 02. Process large documents efficiently
- 03. Build secure document-access controls
- 04. Create a clean and responsive workspace UI
- 05. Reduce unnecessary architectural complexity
- 06. Turn experimental prototypes into production-ready systems
- 🐼 Pandas & Matplotlib
- 🧼 Data cleaning & analysis
- 📄 OCR & document extraction
- 🛠️ Foundry (Forge, Cast, Anvil, Chisel)
- 📈 Chainlink Price Feeds & Chainlink VRF
- 📜 Solidity scripting & contract testing
- 🪟 Windows and WSL
- 🐳 Docker Desktop
- 🐙 Git and GitHub
- 🦙 Ollama (Local LLMs)
- 🔄 n8n automation
- 🌐 Exa web-search integration
- 🔌 REST APIs
- 🐚 PowerShell and Bash scripting
AI · Django · RAG · PDF Processing · Legal Research · Web Search
A document-centred legal AI platform supporting research, source-grounded answers, PDF analysis and drafting workflows.
Solidity · Foundry · Smart Contracts · Testing · Deployment
A collection of Solidity projects developed while learning professional smart-contract workflows with Foundry.
Solidity · Chainlink · Forge Testing · Deployment Scripts
A decentralized funding contract using Chainlink price feeds, automated deployment scripts and unit testing.
Solidity · Chainlink VRF V2.5 · Automation · Foundry
A decentralized raffle system using verifiable randomness, mocks, network configuration and automated testing.
Python · Flask · OpenCV · Tesseract OCR · Pillow
An OCR-based application for extracting digital text from handwritten or scanned images.
Python · Pandas · Matplotlib · SQL
Data-cleaning, visualization and exploratory-analysis projects, including analysis of COVID-19 datasets.
n8n · Gmail · Ollama · Docker · Local AI
Experiments with AI-assisted email categorization and local automation using n8n, Gmail integrations and Ollama models.
| Area | Current Focus |
|---|---|
| AI Engineering | RAG, grounding, retrieval, and model orchestration |
| Backend Development | Django architecture, APIs, and background jobs |
| Document Intelligence | PDF parsing, OCR, indexing, and citations |
| Security | Authentication, authorization, and data isolation |
| Cloud | Deployment, monitoring, and scalable infrastructure |
| Frontend | Responsive AI workspaces and TypeScript |
| Blockchain | Foundry, Solidity, and Chainlink integrations |
| Data | Python, SQL, and data visualization |
Understand the problem
↓
Build the smallest working version
↓
Test it with real inputs
↓
Find architectural weaknesses
↓
Improve security and reliability
↓
Document what matters
↓
Repeat
- Clear architecture over unnecessary abstraction
- Secure defaults over client-controlled trust
- Grounded AI answers over confident hallucinations
- Practical testing over assumptions
- Maintainable code over short-term shortcuts
- Simple interfaces over technical clutter
My current objective is to become capable of building complete real-world systems—from interface and backend architecture to AI integration, security, testing and deployment.
I am particularly interested in projects involving:
AI + Documents · AI + Legal Tech · AI + Automation · Secure Backends · Developer Tools · Open-Source