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$
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I will custom llm chatbot and rag setup
Anurag Nagare
About this gig
Generic chatbots make things up. A chatbot built on your own documents answers from your real information and shows where each answer came from.
I build custom AI chatbots using retrieval-augmented generation (RAG). You give me your PDFs, docs, help-center articles, or website content. I turn them into a searchable knowledge base and connect it to a language model so your team or customers get accurate, sourced answers.
What you can use it for
- Customer support and FAQ bots on your website
- Internal assistants for HR, policies, onboarding, or product documentation
- Document Q&A for contracts, reports, and manuals
- Chatbots for private or sensitive data
Get to know Anurag Nagare
Anurag Nagare
Senior AI and Machine Learning Engineer
- FromIndia
- Member sinceOct 2024
- Avg. response time9 hours
Languages
English
I’m Anurag Nagare — an AI/ML Developer and Python Backend Engineer with a passion for building real-world, intelligent solutions.
I specialize in designing and deploying machine learning models for applications in computer vision, NLP, and generative AI. My experience spans across end-to-end development, from training deep learning models to integrating them into scalable web applications using Flask, Django, and Streamlit.
Over the past few years, I’ve delivered full-time projects involving object detection, content generation using LLMs, real-time inference APIs, and AI-powered dashboards.
My Portfolio
FAQ
Will the chatbot make things up?
RAG greatly reduces this by grounding answers in your documents and showing sources, but no AI system is perfect. I test it on real questions and tune it, and I can set it to say it doesn't know when the answer isn't in your
Do I pay for the AI model separately?
If we use a hosted model, usage fees go through your own account. Open-source models deployed on your server have no per-message fees, but need hosting.
