I will build a custom ai chatbot using your data with rag


About this gig
Generic chatbots fail because they don't know your business. I build custom AI assistants that learn directly from your data.
Using a state-of-the-art Retrieval-Augmented Generation (RAG) system, I'll create a smart chatbot that accurately answers questions based on your internal documents, knowledge base, or website. No more "I don't know"just precise, context-aware answers that can even cite the source.
WHAT I OFFER:
- Custom Knowledge Base: Your bot learns from your PDFs, Docs, or websites.
- Accurate, Factual Answers: Drastically reduces AI "hallucinations" and wrong information.
- Vector Database Integration: Built to handle thousands of documents efficiently.
- Full App Development: From a simple script to a fully deployed web application.
Powered by leading technologies like Python, LangChain, OpenAI (GPT-4o), and Pinecone/ChromaDB.
️Ready for a chatbot that actually works? Message me before ordering, and let's discuss your project to ensure perfect results.
Get to know Anas Stilinski
AI and Big Data Specialist, MSc in Big Data and AI
- FromMorocco
- Member sinceMay 2020
- Last delivery1 year
Languages
English, French, Arabic
FAQ
How is this different from just using ChatGPT?
ChatGPT has no knowledge of your private business information. My service creates a chatbot that combines the power of models like GPT-4o with a secure knowledge base built from your documents, providing answers that are accurate and specific to your business.
Is my data kept private and secure?
Absolutely. Your data is used solely for the purpose of creating your chatbot's knowledge base. I adhere to strict confidentiality standards and use secure cloud infrastructure. Your private data is never used for training public models.
What is a vector database and why do I need one?
A vector database (like Pinecone or ChromaDB) stores your documents in a special format that allows the AI to quickly find the most relevant information when answering a question. It is essential for creating a fast and scalable chatbot that can handle more than a handful of files.
Are there any ongoing costs after delivery?
Yes. A deployed chatbot has two main potential costs: 1) The LLM API usage fees (e.g., from OpenAI), which depend on usage, and 2) The hosting costs for the database and web application. These are typically low for moderate use, and I will help you estimate them.
What kind of documents can the chatbot learn from?
The system can learn from a wide variety of formats, including PDF, Microsoft Word, plain text files, and website content. If you have data in another format (like a database), we can discuss a custom integration.

