Full-stack developer & product designer | AI workflows
AI Engineer | LLMs, RAG & Document Intelligence
AI Engineer | LLMs, RAG & Document Intelligence
Need AI That Solves a Real Business Problem?
I help startups, founders, and businesses build practical AI applications, from intelligent document processing to custom LLM-powered products.
I'm an AI/ML Engineer with experience in Generative AI, RAG, agentic workflows, NLP, and production AI systems. I focus on building solutions that go beyond a basic chatbot or AI demo.
Here's how I can help:
AI Document Intelligence & Automation
Extract structured information from PDFs, invoices, contracts, and business documents.
Automate document-heavy workflows and reduce repetitive manual work.
Build AI pipelines for document understanding, classification, and data extraction.
RAG Systems & AI Knowledge Assistants
Build chatbots that answer questions using your documents and internal knowledge base.
Implement embeddings, semantic search, retrieval optimization, and source-grounded responses.
Create internal knowledge assistants that help teams find information faster.
Custom AI Applications & Agentic Workflows
Develop LLM-powered applications and AI features.
Build multi-step AI workflows with tool integration and structured outputs.
Integrate AI models into Python backends and existing products using FastAPI and APIs.
How I approach projects
I start by understanding the business problem, then define the solution, build the core workflow, and validate it against real use cases. The goal is to deliver something useful, maintainable, and ready for the next stage of development.
One of my projects is Knowra, an enterprise knowledge assistant focused on document intelligence and retrieval-based AI.
If you're building an AI product, automating a business process, or exploring how LLMs could improve your existing software, I'd be happy to discuss your project.
Have an idea? Send me a message on Contra, and let's discuss what we can build.
Portfolio: https://portfolio-6lg.pages.dev/
Github: https://github.com/Ajeeetsingh
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Knowra is my enterprise document intelligence project, designed to help users search and work with information across complex document collections. This screenshot showcases the product interface and its document-focused workflow.
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Full-stack web developer — React, JS, Websites & modern UIs.
New to Contra
Full-stack web developer — React, JS, Websites & modern UIs.
Built a full ecommerce fashion storefront for AL Creations (abaya, hijab & custom wear) — homepage, shop filters, product pages, cart/checkout, WhatsApp ordering, and a client admin to manage products & stock.
Designed for real small businesses who want an Amazon-style shopping experience without Shopify complexity.
Stack: HTML, CSS, JavaScript, React-ready UI patterns, Supabase, Netlify.
Live demo: https://al-creations-store-preview.netlify.app
I help brands launch clean, mobile-friendly websites that convert visitors into orders.
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Built Boomerang — a landing experience for building lasting relationships.
Live demo: https://boomerang-sand.vercel.app/
(https://boomerang-sand.vercel.app/)video walkthrough: https://www.loom.com/share/e3d2389bed1e45e6ab0d04d99228ee92
#webdesign #frontend
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SOFTDROP — soft-launch studio for Gen Z creators.
I built the product I wish existed: drop privately to your circle, collect real heat (would share / would buy / saves), plan soft vs public on Stack, then Forge a caption pack for TikTok / IG / Shorts — with Trend Radar that always says soft launch first.
Flowstep prototype (public):
https://app.flowstep.ai/file?activeFileId=35f205a1-d4b8-4027-8503-8200e6456a5b
(https://app.flowstep.ai/file?activeFileId=35f205a1-d4b8-4027-8503-8200e6456a5b)LinkedIn post: https://www.linkedin.com/posts/share-7488847095685148672-x8Ja/?utm_source=share&utm_medium=member_desktop&rcm=ACoAACkVFsQBZOclokeQuU49ndgFqucqrfHAE1c
Multi-screen clickable flow: Splash → Circle → Stack → Create → Heat → Forge → Aura → Radar.
#flowstepchallenge
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Designed and built shop listing, category filters, and product detail pages for a fashion ecommerce store (abaya, hijab, kids & custom wear).
Focus: clean UI, mobile-friendly layout, clear pricing, and fast path from browse → product → cart.
watch- walkthrogh:https://www.loom.com/share/3f8f06558ae946698e8361f8e9681097
Live demo: https://al-creations-store-preview.netlify.app
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Senior Full Stack Engineer · React, Next.js, AI agents
I build AI systems and cross-platform mobile apps.
I build AI systems and cross-platform mobile apps.
LookInsight AI : AI Customer Support Automation System
Full-stack AI system that automates customer support workflows.
What it does:
→ Classifies customer intent (complaint, inquiry, refund, support) → Detects urgency and routes to the right team
→ Looks up customer history via knowledge graph
→ Generates personalized response drafts in seconds
Key features: • Real-time processing pipeline with live visualization
• Multi-channel support (Email, Twitter, Slack, WhatsApp)
• Business rules engine for tier-based treatment (VIP, Premium, Regular)
• Neo4j knowledge graph for customer context
Tech stack: Python, FastAPI, OpenAI GPT-4, Neo4j, Next.js, TypeScript
Live demo: https://lookinsight.ai
Skills: Python AI OpenAI FastAPI Next.js Customer Support Automation
Link: https://lookinsight.ai
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AI Product Engineer building custom LLM & RAG pipelines.
Project Title:- Custom Enterprise RAG Assistant | Chat with Documents & PDFs
Project Overview: DocuMind is an enterprise-grade Retrieval-Augmented Generation (RAG) assistant designed to eliminate manual data extraction and prevent AI hallucinations. It converts static corporate files (PDFs, reports, resumes, contracts) into an interactive, grounded knowledge engine that provides answers backed by direct page-level citations.
The Problem Solved: * Manual Data Hunting: Eliminates hours spent reading through dense, complex documentation.
AI Hallucinations: Constrains LLM outputs strictly to uploaded context, ensuring reliable, factual data.
Lack of Auditability: Provides exact file names and page references for compliance and verification.
Key Technical Features: * Dynamic Indexing: Fast chunking and local vector embedding using Hugging Face models (all-MiniLM-L6-v2).
High-Accuracy Vector Search: ChromaDB integration for persistent vector storage and low-latency similarity retrieval.
Decoupled Architecture: Asynchronous FastAPI backend paired with a clean, responsive Streamlit chat frontend.
Contextual Synthesis: Powered by Google Gemini (gemini-2.5-flash) for cost-effective inference.
Tech Stack: Python, FastAPI, LangChain, ChromaDB, Hugging Face, Google Gemini, Streamlit.
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🚀 How I Solved the HR Resume Bottleneck with AI
Recruiters waste endless hours manually scanning hundreds of unformatted resumes, often missing strong candidates due to fatigue.
To solve this, I built an AI Resume Screening Agent that automates the heavy lifting:
Semantic Matching: Uses sentence embeddings to understand the true context of skills rather than relying on rigid keyword matching.
Instant Leaderboard: Automatically parses multiple PDF resumes, computes match scores, and ranks candidates from best to worst.
Actionable AI Feedback: Instantly generates structured breakdowns of candidate strengths, missing skill gaps, and hiring recommendations using the Groq API.
Workflow Efficiency: Condenses hours of sorting into seconds with a one-click CSV report export.
🛠 Tech Stack: Python, FastAPI, Groq, SentenceTransformers, Pandas, HTML/CSS.
Check the comments for the live public link to test it yourself! What tools do you use to speed up hiring?
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Hi, I'm Mirwaise Khan, an AI engineer building practical tools with large language models.
This is a project I built — an Enterprise AI Document Assistant. You upload any PDF, and it indexes the content using ChromaDB and vector embeddings.
Then you can ask it questions in plain English, and it retrieves the exact relevant section and gives you a grounded answer — with the source cited, so you always know where the information came from.
I build systems like this — RAG pipelines, AI chatbots, and document automation tools — using Python, LLMs, and vector databases.
If you need something like this for your business, let's talk.
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AI Invoice Data Extraction Dashboard
Built an AI-powered tool that automatically extracts key data from PDF invoices — vendor name, invoice number, date, tax, and total amount — and displays it in an editable dashboard for quick review before saving. Users can upload any invoice PDF, get instant structured extraction, correct fields if needed, and export clean data straight to CSV.
Tech used: Python, GenAI/LLM extraction, Pandas, PDF parsing, Streamlit/web UI
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AIML @ RVCE | Building Private, High-Performance Local AI
AIML @ RVCE | Building Private, High-Performance Local AI
Vision-Cart V2: Neural Intelligence Platform
Developed a high-end Visual Auditing dashboard for retail and industrial quality control. Unlike basic classifiers, this system performs Deep Feature Extraction—calculating metrics like caffeine content (mg), volume (ml), and shelf fill-levels.
Edge-AI Mastery: Optimized to run Ollama (Moondream) locally on restricted hardware (2GB VRAM), ensuring total data privacy.
Industrial UI: Built a 'Nuvion-Black' interface with real-time scanning animations and a horizontal Bento-grid for system vitals.
Business Logic: Integrated a 'Neural Suggestion' engine to turn visual scans into automated inventory and QC decisions.
Tags: #ComputerVision #EdgeAI #React #FastAPI #MachineLearning
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The Culinary Hub: High-Performance, Commission-Free Cafe Engine
Project Description
The Problem: Local cafes lose ~30% revenue to aggregator commissions (Zomato/Swiggy).
The Solution: A high-fidelity "Emerald Glass" storefront designed for direct customer conversion.
Key Features:
Zero-Commission Engine: Structured WhatsApp ordering to bypass third-party fees.
Operational Logic: Real-time "Shop Status" toggle to manage kitchen hours automatically.
Premium UI: Glassmorphism design built with Tailwind CSS for a mobile-first, luxury feel.
Loyalty Focused: Built-in "Order Your Usual" feature via local storage for repeat customers.
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SkyFlow | End-to-End Flight Engine
The Goal: A high-performance booking journey from search to seat selection.
The Tech: Powered by Python (Flask) and Amadeus API for real-time global flight data.
Key Features:
Interactive Seat Mapping & real-time price fetching.
Automated Ticket Generation & booking management.
"Soft-Luxury" UI designed with Tailwind CSS for mobile responsiveness.
The Result: A seamless, professional-grade flow built for speed and reliability.
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Premium Hospitality Landing Page Template
The Project: A high-performance, mobile-responsive landing page designed for the hospitality industry.
Built with a focus on "Soft-Luxury" aesthetics and high-speed performance.
Key Tech: HTML5, CSS3, JavaScript, and Netlify for deployment.
Top Feature: Commission-free WhatsApp booking integration to drive direct customer reservations.
Try it yourself: https://demo-cafes-123.netlify.app/
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Turning ideas into scalable web systems
Turning ideas into scalable web systems
Project Goal:
Designed and developed a full-stack, AI-powered e-waste management platform to promote responsible electronic waste disposal while enabling value recovery, recycling discovery, and convenient pickup services.
• Built RESTful backend APIs using FastAPI / Node.js for authentication, classification workflows, facility management, pickup scheduling, and marketplace operations
• Integrated an AI image classification model to categorize e-waste into recyclable, reusable, or hazardous types
• Implemented a facility locator with map integration to identify nearby certified recycling centers
• Developed a rule-based value estimation engine for resale and scrap pricing
• Created a slot-based pickup scheduling system with confirmation flow
• Integrated Razorpay payment gateway for secure online transactions
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Audio / Text to Indian Sign Language Converter
Built a web-based accessibility application that converts audio and text into Indian Sign Language (ISL) to help improve communication for people with hearing impairments.
The system uses the Web Speech API for speech-to-text conversion and applies NLP techniques to process and simplify text before mapping it to corresponding ISL gesture animations for clear visual output.
Tech stack: Django, JavaScript, HTML, CSS, NLTK
Focused on accessibility, inclusivity, and real-world usability.
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File Management & Sharing Web App
Built a web-based application to upload, organize, manage, and share files securely with folder support.
Key features:
• Upload multiple files at once to folders or root
• Create and delete folders dynamically
• Download and delete files easily
• Generate shareable links with expiration
• Copy share links instantly to clipboard
Cloud & backend:
Files stored securely in AWS S3
Metadata managed in MongoDB
Backend built with Node.js & Express
Frontend:
Responsive UI using React and Tailwind CSS
Designed for scalability, secure file handling, and smooth user experience.
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