I will build an ai sales agent with rag and llm integration


About this gig
I will build an AI Sales Assistant powered by RAG to automate customer conversations, answer product questions, and provide intelligent recommendations.
Tech Stack:
- Python (FastAPI) for backend development
- OpenAI / Claude LLMs for AI responses
- LangChain for RAG pipeline orchestration
- Vector databases (Pinecone, FAISS, ChromaDB) for knowledge retrieval
- PostgreSQL / SQL databases for data management
- APIs for CRM, website, and third-party integrations
Workflow:
- Data Processing - Collect and clean your documents, FAQs, product catalogs, and business data.
- Knowledge Base - Creation Convert data into embeddings and store them in a vector database.
- RAG Implementation - Retrieve relevant information and generate accurate AI responses using LLMs.
- AI Assistant Integration - Connect the chatbot with your website, CRM, WhatsApp, or other platforms.
- Testing & Optimization - Improve response quality, accuracy, and user experience.
Benefits You Get:
- 24/7 AI-powered customer support and sales assistance
- Faster responses to customer questions
- Accurate answers based on your business data
- Automated lead qualification and product recommendations
- Reduced manual support workload
Get to know Marko
Top Rated Fullstack, AI Agent Developer
- FromSerbia
- Member sinceJun 2026
- Avg. response time1 hour
Languages
Serbian, English
My Portfolio
FAQ
What is an AI Sales Assistant?
An AI Sales Assistant is a chatbot that uses AI and your business data to answer customer questions, recommend products, and help generate leads.
What data do you need to build the AI assistant?
I need your product catalog, FAQs, website content, documents, or any business knowledge you want the AI to use.
Can the AI assistant recommend products?
Yes, it can analyze customer queries and provide relevant product recommendations based on your data.
Can you integrate it with my website or CRM?
Yes, I can integrate the AI assistant with websites, CRMs, WhatsApp, APIs, and other business platforms.
What technology do you use?
I use Python, LangChain, OpenAI/Claude models, vector databases (Pinecone, FAISS, ChromaDB), and API integrations.
Will the AI provide accurate answers?
Yes, the RAG approach retrieves information from your knowledge base to generate more accurate and context-aware responses.
Can I update the AI knowledge base later?
Yes, your documents, products, and business information can be updated anytime to improve the assistant.

