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I will develop a custom rag for your business
Mohammad Imran
About this gig
Looking to build an AI-powered RAG system that can understand your business documents and database? I can help you build a reliable, scalable RAG solution tailored to your needs.
What I Build
- Custom RAG & AI Knowledge Systems
- Document & Database-based RAG
- Multi-format Document Processing
- LLM & API Integrations
- AI Agents & Intelligent Workflows
Tech Stack
Python · JavaScript · LangChain · LangGraph · Node.js · MongoDB · PostgreSQL · Supabase · GenAI
Whether you need a document Q&A chatbot, internal knowledge assistant, or AI-powered business search, I focus on building practical solutions that deliver accurate and useful results.
Message me before placing an order so we can discuss your requirements and choose the right RAG architecture for your project.
Get to know Mohammad Imran
Mohammad Imran
Senior React, NextJs Developer, Fullstack Developer having 5 YOE
- FromIndia
- Member sinceJan 2024
- Avg. response time1 hour
Languages
English, Urdu, Hindi, Telugu
I’m a Senior React & Next.js Developer with 5+ years of enterprise experience building scalable, high-performance web applications. I specialize in React.js, Next.js, TypeScript, JavaScript, Redux Toolkit, Tailwind CSS, responsive UI, and Figma-to-React development. I build modern websites, SaaS platforms, dashboards, and custom web applications with clean, maintainable code. I also work with REST APIs, third-party integrations, and AI-powered applications including LLM and RAG integrations.
My Portfolio
FAQ
What do you need from me to get started?
I’ll need your requirements, documents or data source, preferred AI model (if any), and details about how you want users to interact with the RAG system.
Can you build a RAG system using my business documents or database?
Yes. I can build RAG solutions using PDFs, Word files, text, websites, or structured business data such as MongoDB and PostgreSQL.
Can I use my own LLM or API?
Yes. I can integrate models and APIs such as OpenAI, Gemini, Claude, or locally hosted models depending on your project requirements.
Can you integrate the RAG system into my existing application?
Yes. I can integrate the RAG backend with your existing web application, APIs, database, or frontend.
Will the RAG system provide accurate answers from my data?
I’ll design the retrieval process to provide relevant context to the LLM and reduce irrelevant or hallucinated responses. However, accuracy depends on the quality, structure, and completeness of your data.
