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English
$
USD
I will build rag ai chatbot using openai, langchain, and vector database
Emily
About this gig
Looking for a powerful RAG (Retrieval-Augmented Generation) AI chatbot that delivers accurate, context-aware responses from your own data? You're in the right place!
I specialize in building custom RAG AI chatbots using OpenAI, LangChain, and vector databases to help businesses create intelligent assistants for customer support, internal knowledge bases, document search, and business automation.
What I can build:
- Custom RAG AI chatbots
- OpenAI GPT integration
- LangChain-powered applications
- Vector database integration (Pinecone, ChromaDB, FAISS, Qdrant, and more)
- PDF, Word, Excel, and website knowledge base chatbots
- Website and web app chatbot integration
- API and database connectivity
- Secure, scalable, and production-ready AI solutions
Why choose me?
- Clean and well-documented code
- Fast delivery and clear communication
- Scalable architecture
- Secure API and data handling
- Post-delivery support
Before placing your order, please contact me to discuss your project requirements. I'll recommend the best RAG architecture and deliver a custom AI chatbot tailored to your business needs.
Get to know Emily
Emily
AI Automation ChatGPT API RAG Chatbots n8n LangChain Expert
- FromUnited Kingdom
- Member sinceJul 2026
- Avg. response time1 hour
Languages
English
I'm an AI developer specializing in workflow automation, ChatGPT API integration, and RAG AI chatbot development. I build intelligent solutions using OpenAI, LangChain, n8n, Make.com, and vector databases to help businesses automate processes, improve customer support, and unlock insights from their data. My focus is delivering secure, scalable, and high-quality AI solutions with clean code, reliable performance, and excellent communication from start to finish.
Other AI Development Services I Offer
FAQ
What is a RAG AI chatbot?
A RAG (Retrieval-Augmented Generation) chatbot uses your documents, databases, or knowledge base to provide accurate, context-aware responses powered by OpenAI and LangChain.
What types of data can my chatbot use?
Your chatbot can retrieve information from PDFs, Word documents, Excel files, websites, databases, Notion, Google Drive, APIs, and other supported knowledge sources.
Which vector databases do you support?
I can work with popular vector databases such as Pinecone, ChromaDB, FAISS, Qdrant, Weaviate, and other solutions based on your project requirements.
Can you integrate the chatbot into my website or application?
Yes. I can integrate your RAG AI chatbot into websites, web applications, dashboards, CRMs, or other business systems.
Will I receive the source code?
Yes. Source code is included according to your selected package, along with deployment guidance if applicable.
