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AI & Full Stack Developer Building Production-Grade Software for Startups

I'm Niraj Kumar — a software developer shipping production-grade Next.js apps, RAG chatbots, LangChain agent systems, and n8n automation pipelines. From architecture to deployment, I deliver AI and full stack systems that handle real users and real data.

Need a developer who can turn an idea into shipped software? Let's talk.

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Turn Your Idea Into a Scalable Product

I help businesses build modern web, mobile, and AI applications that grow with their users and goals — delivering end-to-end engineering solutions from architecture to deployment, focused on solving real business problems, not just writing code.

Full Stack Development

Web Application Development

Complete web application solutions built with modern technologies. We create scalable SaaS platforms, business portals, and customer-facing applications using React, Next.js, TypeScript, and Redux. Our solutions include user authentication (Auth0, Firebase), subscription management (Stripe, Paddle), role-based permissions, and secure data handling for businesses of all sizes.

Deliverables

  • Next.js & React architecture
  • Auth0 / Firebase authentication
  • Stripe / Paddle integration
  • Admin dashboards
  • REST / GraphQL APIs
  • PostgreSQL / MongoDB

Best for: Startups, growing businesses, enterprise teams

AI & Machine Learning

AI Chatbots & Intelligent Assistants

Custom AI solutions that understand and respond to user needs. We build conversational AI systems using LangChain, OpenAI, and Anthropic Claude that access your business data, answer questions, and automate support workflows. Solutions include RAG (Retrieval Augmented Generation) for document understanding and can be deployed on your infrastructure for complete data privacy.

Deliverables

  • LangChain / LangGraph pipeline
  • OpenAI / Claude integration
  • RAG knowledge base
  • Document processing
  • Conversation analytics
  • Secure deployment

Best for: Customer support automation, internal knowledge systems

Cloud & Infrastructure

Cloud Infrastructure Setup

Professional cloud infrastructure on AWS, Google Cloud, or Azure. We implement Docker containerization, Kubernetes orchestration (EKS, GKE, AKS), automated CI/CD pipelines (GitHub Actions, GitLab CI), and infrastructure-as-code with Terraform. Built for reliability, security, and compliance requirements.

Deliverables

  • AWS / GCP / Azure setup
  • Kubernetes (EKS/GKE/AKS)
  • Terraform infrastructure
  • GitHub Actions CI/CD
  • Auto-scaling & load balancing
  • Disaster recovery

Best for: Production applications, scalable systems, regulated industries

Specialized Stacks

Looking for a specific stack?

Dedicated guides for the work I do most often — pick the stack closest to your project.

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Build Faster. Ship Confidently.

Pre-built systems for immediate deployment. Plus: live demos of production work.

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Coming Soon

Products are being prepared and will be available shortly. Check back soon or reach out to discuss a custom build.

Request Custom Build

Why Work With Me

01

Business-first mindset

I build solutions around your goals and ROI, not just the tech.

02

AI + Full Stack

Rare combination — I can architect, build, and deploy end-to-end AI systems.

03

Production experience

I've shipped real systems that handle real users and real data.

04

Clean, scalable code

Well-structured, documented, and maintainable.

Practical Insights for Building Better Products

Actionable guides on shipping faster, scaling smarter, and solving real business challenges — written for founders and teams who value results over hype.

Read the Blog →

Frequently Asked Questions

Everything founders and product teams ask before hiring me.

How much does an AI development project cost?

For most production AI projects (RAG chatbots, LangChain pipelines, agent systems), engagements typically range from ₹40,000 for a tightly scoped MVP to ₹4,00,000+ for a multi-month full stack build. I offer fixed-price, hourly, and retainer models — request a free estimate on the contact page.

How long does it take to build a RAG chatbot?

A standard RAG chatbot — ingestion pipeline, vector store (pgvector or Pinecone), retrieval, citations, and a chat UI — takes 2–3 weeks. Adding agent loops, evaluation harnesses, or fine-tuning extends the timeline.

What tech stack do you use?

Frontend: Next.js (App Router), React, TypeScript, Tailwind. Backend: Node.js, Python (FastAPI). AI: LangChain, LangGraph, OpenAI, Anthropic Claude, Ollama, pgvector, Pinecone. Infra: Docker, AWS, Vercel, GitHub Actions. Automation: n8n.

Do you work with startups or enterprises?

Both. I've shipped production systems for early-stage startups (auth, billing, AI features) and worked inside enterprise teams. Most engagements are remote and async-first.

Do you sign NDAs and handle data privacy?

Yes. I sign NDAs before any technical discussion involving proprietary data, and I support self-hosted deployments (Ollama, vLLM) for clients who can't send data to third-party LLM APIs.

Let's Build Something Great

Have an idea, project, or business problem? Let's discuss how I can help you build it.

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