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I will create rag based chatbot for your business


About this gig
Grow Your Business with a Custom RAG Chatbot
Provide instant, accurate information to your customers with a powerful Retrieval-Augmented Generation (RAG) chatbot. Unlike traditional chatbots, a RAG chatbot uses your own private data to provide context-aware and highly accurate answers, eliminating "hallucinations" and providing factual, up-to-date information.
What We Offer
Whether you need a simple prototype or a fully deployed solution, we offer a range of services:
- Complete Chatbot Prototype: Get a complete, working RAG chatbot prototype in a Python Notebook. This includes the retrieval and generation pipeline using your data.
- API & Interface: We'll create a complete chatbot with a user-friendly frontend interface and a robust API (backend).
- Memory of Previous Messages: Your chatbot will remember conversation context for more natural and meaningful interactions.
- Full Deployment & Integration: We'll integrate the chatbot with your website and handle the full deployment process, ensuring it's live and ready to serve your customers 24/7.
Stop losing customers to slow response times and generic answers. Let's build a smart, reliable RAG chatbot that understands your business.
Get to know Amaan
Full Stack AI Engineer, Architecting High ROI AI Systems and Automations
- FromPakistan
- Member sinceJan 2023
- Last delivery11 months
Languages
Urdu, English
My Portfolio
FAQ
Can you integrate the chatbot into my existing website?
Yes. The complete deployment package includes integration with your website, allowing your customers to interact with the chatbot directly on your platform.
How long will it take to build my chatbot?
The timeline depends on the complexity of your project and the specific package you choose. I will provide a detailed timeline and delivery schedule after discussing your requirements.
What is a RAG chatbot, and how is it different from a regular chatbot?
A RAG chatbot combines a large language model with your data, retrieving information from your documents to generate precise, relevant answers. This approach reduces inaccuracies and provides factual, up-to-date responses, unlike a standard chatbot that relies on pre-trained data.
What kind of data can I use for the chatbot?
The chatbot can be trained on a variety of data sources, including PDFs, Word documents, text files, and website URLs. The more comprehensive and organized your data, the better the chatbot's performance will be.
How does the "previous message memory" feature work?
The previous message memory allows the chatbot to remember the context of the conversation. It stores a history of the user's recent messages, enabling it to provide more coherent and context-aware responses, leading to a more natural and productive conversation.
