I build MVPs in 2-4 weeks |Shipped 50+ MVPs for 30+ clients
I build MVPs in 2-4 weeks |Shipped 50+ MVPs for 30+ clients
Full-stack software developer
Full-stack software developer
AI Lead Automation for Service Businesses
AI Lead Automation for Service Businesses
Client project - OM Mobile Store (Phansidewa, India). Built a mobile-first store website for a local smartphone retailer that turns visitors into orders and calls. Brand-wise catalog (Apple, Samsung, Vivo, Oppo and more) with prices and variants, cart with Cash on Delivery, 24-hour delivery messaging, and one-tap Call, WhatsApp and Shop buttons always on screen. Added a voice assistant and chat widget so customers get answers instantly instead of waiting for a callback. Live at ommobile.store
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Client project - UE Asia (Bengaluru, India). Built a B2B lead-generation website for an authorised NSK-RHP & THK bearings distributor supplying industry since 1998. Buyers can search the catalog by part number, brand or category, add parts to an RFQ cart and request a quote, or send their requirement straight to WhatsApp. A chat widget captures enquiries 24/7 and every lead lands with the sales team, backing their 2-hour quote turnaround promise. Built mobile-first and SEO-ready. Live at ue-asia.in
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Client project - SAI Mobile Mart (Falakata, India). Built a full e-commerce store for a local smartphone & electronics retailer with AI built in. A 318+ product catalog with brand/category filters and search, cart, 0% EMI calculator, festive offers and a daily lucky-wheel coupon. Added an AI voice assistant (Priya AI Voice) and an AI chatbot so shoppers get instant answers and the store captures every enquiry, plus a store CRM/admin panel to manage inventory and leads. Same speed-to-lead stack I deploy for service businesses. Live at saimobilesmart.tech
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Book Roofing Appointments in Minutes with AI
This demo showcases a fully responsive roofing website where homeowners can book inspections directly from their mobile devices using an AI-powered chatbot integrated with Calendly.
The experience is designed to reduce response times, automate scheduling, and make it easier for roofing companies to convert website visitors into booked appointments.
Features
📱 Fully responsive mobile design
🤖 AI chatbot for instant customer assistance
📅 Calendly appointment scheduling
🏠 Roofing inspection booking workflow
⚡ Fast and intuitive user experience
📧 Automated appointment confirmation
📊 CRM-ready lead capture
🔒 Secure and scalable implementation
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Fullstack Engineer: Turning Ideas into Reality
Fullstack Engineer: Turning Ideas into Reality
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Next.js Expert: Fast, Scalable Web Solutions
Next.js Expert: Fast, Scalable Web Solutions
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Technical lead 10+ years of experience building software
Technical lead 10+ years of experience building software
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Senior Full-Stack, AI & Mobile App Developer | 10+ Yrs
Eco Village – Real Estate Website Development
Designed and developed a modern, responsive website for Eco Village, a premium real estate township project. The website was created to showcase the project's vision, amenities, property information, and investment opportunities while delivering an engaging user experience.
🔹 Key Features:
• Responsive Website Design
• Project Showcase Pages
• Amenities & Facilities Section
• Lead Generation Forms
• SEO-Friendly Structure
• Fast Loading Performance
• Mobile-Friendly User Experience
Technologies Used:
React.js, Next.js, JavaScript, Node.js, Bootstrap
Live Website:
https://eco-village.co.in
Role:
Frontend & Full Stack Website Developer
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Step To Soft – Software Development & IT Services Platform
Developed and maintained a professional software development and IT services platform showcasing web development, mobile app development, AI solutions, cloud services, and dedicated development teams.
🔹 Key Features:
• Company Portfolio Website
• Service Showcase Pages
• Dedicated Developer Hiring
• Web & Mobile Development Services
• SEO-Friendly Architecture
• Responsive UI/UX
• Lead Generation & Contact System
Technologies Used:
React.js, Next.js, Node.js, JavaScript, TypeScript, MongoDB, REST APIs
Live Project:
https://www.steptosoft.com
Role:
Full Stack Developer
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Marengo Asia Hospitals – Healthcare Website Platform
Developed and maintained a modern healthcare and hospital management web platform for Marengo Asia Hospitals. The platform provides seamless access to hospital information, doctor search, appointment booking, patient services, and healthcare resources.
🔹 Key Features:
• Hospital & Doctor Search
• Online Appointment Booking
• Patient Portal Integration
• Responsive User Interface
• Multi-location Hospital Management
• SEO-Friendly Architecture
• Performance Optimization
Technologies Used:
React.js, Next.js, Node.js, JavaScript, REST APIs, Bootstrap
Live Project:
https://www.marengoasiahospitals.com
Role:
Full Stack Developer
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Deal On Property – Real Estate Marketplace Platform
Developed a modern real estate marketplace platform that helps users buy, sell, rent, and lease properties. The platform features advanced property search, filters, property listings, user authentication, admin dashboard, and responsive UI/UX.
🔹 Key Features:
• Property Buy, Sell, Rent & Lease Listings
• Advanced Search & Filtering
• User Authentication & Authorization
• Admin Dashboard
• Property Image Upload
• Responsive Design
• SEO-Friendly Architecture
Technologies Used:
React.js, Next.js, Node.js, Express.js, MongoDB, JavaScript, Bootstrap, REST APIs
🌐 Live Project:
https://dealonproperty.com
👨💻 Role:
Full Stack Developer
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Full-stack developer and founder building real-world product
New to Contra
Full-stack developer and founder building real-world product
Built for the Accenture Innovation Challenge (Round 2), this one tackles a problem most companies rolling out AI don't think about until it bites them: if you're running several different LLM-powered features at once — a customer support bot, an internal knowledge assistant, a tool inside a regulated decision workflow — each one needs a completely different level of scrutiny. A support bot can tolerate more risk and needs to respond fast; a regulated decision-support tool needs to be slow, careful, and willing to hold a response for human review rather than guess.
AuRizz is a middleware layer that sits between an enterprise's LLM provider and its users and decides, per use case and in real time, whether a generated response should go through as-is, get redacted, get held for a human, or get blocked outright.
What made this a genuinely hard build, not just an API wrapper:
Policy-driven, not hardcoded. Every behavioral difference between use cases — which checks run, their thresholds, what happens on failure — lives in YAML config, not in application code. Switching a deployment's risk posture is a config edit, not a redeploy.
Confidence as a first-class signal. Every check returns both a risk score and a confidence in that score — a high-risk-but-unsure reading routes to human review instead of auto-blocking, which is the actual fix for alert fatigue.
Multi-provider by design. Works with Anthropic, OpenAI, Gemini, or Groq behind one interface, with automatic runtime fallback if a provider fails — switching providers is a one-line config change, not a rewrite.
A real audit trail. Every decision is written to a hash-chained, tamper-evident log, and human overrides are appended as new records rather than edits — so the fact that the system said block and a human said allow is preserved, not erased.
Built to be tested. 104 tests run the full pipeline — detectors, aggregation, decision rules, the audit chain — with no network calls or API keys required, because everything is built against interfaces, not vendor SDKs directly.
I worked on this with a teammate — I focused on architecture, pipeline, backend, and we split the detector logic, policy engine, and audit system between us.
Stack: Python, FastAPI, React, TypeScript, Pydantic, SQLite, multi-provider LLM integration (Anthropic/OpenAI/Gemini/Groq)
Status: this is a working prototype, not a deployed product — the source is public and the full pipeline runs locally with real API calls or offline in the test suite, but it hasn't been hosted or put in front of real traffic yet.
If you're building anything where AI output needs a guardrail — content moderation, compliance-sensitive automation, multi-agent systems that need oversight — this is exactly the kind of system design problem I enjoy.
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During my internship at Neosophical Labs, I single-handedly built Sabse Bada Fan (https://sbf.ahoum.com/)(SBF), a live multiplayer quiz game, taking it entirely from an initial idea to a fully launched application. I designed the system to handle over thousands of people playing at the exact same time without slowing down, and I made sure the live leaderboards update instantly for everyone. To make the game accessible everywhere, I integrated Capacitor to seamlessly package the web platform into native Android and iOS mobile apps. Finally, I built an automated background system that perfectly runs our scheduled live quizzes and handles all the scoring completely on its own without any human effort.
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I built this because I was annoyed.
I was paying monthly for a study library seat, and I still couldn't reliably tell if a seat would be free when I showed up. No way to check online, no way to book ahead just calling around or walking in and hoping. I figured if this was frustrating me, it was frustrating thousands of students across India who rent library/reading-room seats the same way.
So I built Studoo (https://studoo.aithro.in/)and Padhloo (https://padhloo.aithro.in/)two connected products at Aithro (https://aithro.in/products)-
Padhloo (student side): search study spaces by city/price/amenities, see a live seat map, request a specific seat for 1-12 months, and track your bookings, dues, and payments in one place. It also gamifies actually showing up — QR check-in/out, study streaks, points, badges, a leaderboard — so students stay consistent, not just book-and-forget.
Studoo (owner side): the dashboard library/reading-room owners use to list their space, manage seat inventory and pricing per slot, approve or reject booking requests, chase due payments automatically, and see real analytics (occupancy, revenue, which slots to reprice). Free tier + two paid plans. You can see product demo video here - https://youtu.be/9Yex73MIYqQ?si=jfWqLxisRTM9N_28
I designed and built the full product end-to-end — the booking/approval workflow, the seat-and-slot inventory model, the QR-based geofenced attendance system, the payments/dues tracking, the subscription tiers, and the whole gamification layer (points, streaks, badges) on the student side.
Where it stands:
Got our first paying customer, a real library owner in Patna paying for the Growth plan, which is the moment this stopped being a side project and started being a business.
Reached the Grand Finale of Empresario 2026 (IIT Kharagpur E-Cell), selected out of 3,000+ global registrations.
Won the Platinum Jubilee Innovation Challenge (Deep Tech) at IIT Kharagpur's 75th anniversary event.
What I'm good at, based on building this: turning a messy real-world workflow (owner approves seat → student pays offline → both sides need to trust the same numbers) into a system that's simple enough for a small business owner with no tech background to actually use — while still handling the edge cases (partial payments, overlapping slots, expiring bookings, geofenced check-ins) correctly under the hood.
If you're a small business or founder who needs a web app or an AI-automation workflow built and shipped fast, not just prototyped that's exactly the kind of problem I like solving. Happy to talk about your project.
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SpeakYield - voice-first agri-commerce platform for Indian farmers
This one came out of a government hackathon problem statement, but the problem itself is real and ugly: a smallholder farmer in Maharashtra selling onions knows yesterday's price at exactly one mandi, usually from the same commission agent who's also buying from them. They can't see the market 40km away, can't see what a processor or exporter would pay, and often sell right after harvest at the seasonal low because they need cash now, not because it's the best time to sell. Every step of that chain - price, buyer trust, quality grading, transport, payment - quietly leaks money out of the farmer's pocket.
I built SpeakYield to close that gap, and built it voice-first because the people this is for often can't or won't use a text-heavy app. A farmer can literally say "I want to sell 12 quintals of onion, I need ₹40,000 right now" in Marathi/Hindi, and the app:
Parses that into a structured request and reads it back for confirmation before anything commits - nothing moves on a guess
Shows every nearby buyer's price as net-in-hand, after transport, commission, and fees - not the misleading headline mandi rate
Recommends sell-now / split / hold based on the farmer's actual cash need, not just a price chart
Ranks competing buyer offers by what the farmer actually banks, weighted by the buyer's payment-reliability history
Runs the full deal lifecycle — offer, logistics, milestone payments, dispute filing — on one transparent, tamper-evident record
What I built: the full stack — Next.js/TypeScript frontend, FastAPI backend, the voice pipeline (speech-to-text → LLM intent parsing with strict schema validation → text-to-speech read-back), the buyer-matching and net-price ranking engine, and the deal/ledger system. Solo project, ~12 commits from architecture to a working two-sided prototype (farmer view + buyer view), with CI, linting, and end-to-end tests.
Stack: Next.js, TypeScript, FastAPI, Python, LLM-based voice intent parsing, PostgreSQL/Redis (production design)
I like this kind of problem specifically because it's not "build a CRUD app" — it's translating a messy, high-stakes, low-trust real-world transaction into software that has to work for someone with a ₹6,000 phone and patchy network, not a power user.
If you need someone who can take a genuinely fuzzy problem (multi-party trust, real-time matching, voice/AI interfaces) and turn it into a working product fast, that's exactly this.
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