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I will develop intelligent ai chatbots using llms, rag, and your custom data
Subham
About this gig
I will build a custom AI chatbot using Retrieval-Augmented Generation (RAG) and Large Language Models (LLMs) like Gemini or Groq. The chatbot will understand and respond to user queries based on your documents or data, using techniques like document parsing, vector embeddings, and intelligent response generation. I use Python, Django, and PostgreSQL for backend development, with deployment options via Azure. Whether you need a simple document-based Q&A bot or a fully scalable GenAI solution, I offer complete integration from source code to cloud deployment. Ideal for business automation, support bots, internal knowledge access, or AI assistants tailored to your workflow. Youll get clean, production-ready code, a user-friendly interface, and post-delivery support. I also offer prompt tuning, multi-document search, admin panels, and chatbot analytics as add-ons. Let's bring your AI chatbot idea to lifeaccurate, secure, and built to scale.
Get to know Subham
Subham
- FromIndia
- Member sinceAug 2025
Languages
Hindi, Oriya, English
GenAI executive with hands-on experience in building RAG chatbots and working with large language models. Skilled in using APIs like Gemini and Groq to develop smart, context-aware systems. Proficient in document parsing, embedding creation, and AI-driven response generation. Strong backend skills with Django and PostgreSQL. Experienced in deploying scalable apps on Azure and managing workflows using Docker, Kubernetes, Jenkins, and Argo CD. Also skilled in Python, Java, JavaScript, and ReactJS. Open to freelance AI and analytics projects.
FAQ
What type of chatbot will you build?
I build custom Retrieval-Augmented Generation (RAG) chatbots using LLMs. These bots can answer questions based on your documents, files, or internal data using intelligent, context-aware responses.
What do I need to provide to get started?
You’ll need to share the documents or data you want the chatbot to understand (PDFs, text files, etc.), along with any specific use case or questions you expect users to ask.
Can you deploy the chatbot on my cloud or website?
Yes! I can deploy it to your preferred environment, including Azure, Docker, or even integrate with your website or internal tools. Let me know your requirements.
Do you support integration with Gemini, Groq, or OpenAI?
Yes, I can integrate your chatbot with Gemini, Groq, or other LLM APIs depending on your preference or budget. I can also help with API key management and environment setup.
Can the chatbot handle multiple documents?
Absolutely. For Standard and Premium packages, I support multi-document ingestion and semantic search across large data sets.
What is Retrieval-Augmented Generation (RAG)?
RAG combines document retrieval with language generation. It allows the chatbot to pull relevant information from your data (PDFs, docs, etc.) and generate accurate, natural language responses using an LLM.
Do you offer chatbot UI design or just backend logic?
I offer both. If you need a chatbot interface (web-based), I can build it using React.js or a simple frontend. Otherwise, I can deliver backend API endpoints ready to connect to your own UI.
Is my data secure?
Absolutely. Your files and content remain confidential. I never reuse client data, and I can follow additional security measures or sign NDAs if needed.
