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Fiverr Pro
English
$
USD
I will build a custom ai chatbot using gpt, rag, and langchain
Eeman Abdullah
About this gig
Are you looking to connect your business data with powerful AI models? I specialize in building custom Retrieval-Augmented Generation (RAG) pipelines, AI chatbots, and intelligent automation systems tailored to your exact needs.
What I Can Build For You:
- Custom RAG Systems: Query your PDFs, internal docs, or databases privately.
- Multi-Agent Workflows: Autonomous AI execution using LangGraph and LangChain.
- Framework & Model Support: OpenAI (GPT-4o), Google Gemini, Claude, and local Llama 3 via Ollama.
- Production Integration: Dockerized FastAPI backends ready for web or mobile apps.
Why Choose Me?
- High-Performance & Clean Code: Modular Python architecture with complete documentation.
- Vector Search Expertise: Vector databases including Qdrant and ChromaDB for instant semantic search.
- Privacy-Focused: Local model setups available for complete data protection.
Please send me a message before placing an order so we can discuss your project scope!
Get to know Eeman Abdullah
Eeman Abdullah
I build AI chatbots, RAG systems, and workflow automations
- FromPakistan
- Member sinceJul 2026
Languages
English
I am an AI ML engineer focused on Retrieval Augmented Generation, LLM integrations, and agentic AI systems. I build pipelines using LangChain, LangGraph, Qdrant, ChromaDB, and FastAPI, and automate workflows with n8n, Make, and OpenAI or Gemini APIs. My projects include a multi agent research platform, a local RAG system for financial documents, and a legal document assistant. I offer chatbot development, RAG pipelines, workflow automation, and LLM integration.
FAQ
Q: Do I need to provide my own API keys (OpenAI, Gemini, etc.)?
A: Yes, you will need to provide your own API keys. I will guide you on how to set them up securely in a .env file so your keys remain completely private.
Q: Can you build an AI system that runs locally with total data privacy?
A: Absolutely! I can set up local LLMs using Ollama (such as Llama 3) along with local vector databases like Qdrant or ChromaDB so no data ever leaves your machine.
Q: What formats of documents can the RAG system process?
A: I can configure the system to parse PDFs, CSVs, TXT files, DOCX documents, web pages, or database records.
