Browse categories
Explore
Fiverr Pro
English
$
USD
I will build ai agents, rag and multi agent systems with langchain langgraph
Rohma T
About this gig
Most AI chatbots just wrap a model they answer plausibly, hallucinate confidently, and can't actually do anything. You need an agent that reasons, uses your real data, and acts.
I build AI agents, RAG systems, and multi agent systems with LangChain and LangGraph:
Grounded RAG answers only from your PDFs, websites & databases, cites every source, and says "I don't know" instead of inventing facts
Tool use searches your knowledge base, calls APIs, updates your CRM, executes multi-step tasks
Memory & state LangGraph agents with persistent memory, branching, retries, and human approval controlled workflows, not fragile prompt chains
Multi agent systems specialized agent teams (researcher + writer + reviewer) that automate whole workflows
Private AI local LLMs (Llama, Mistral via Ollama) so your data never leaves your servers
Stack: LangChain · LangGraph · LangSmith · GPT-4 · Claude · Gemini · Ollama · Pinecone · pgvector · Chroma · FAISS · FastAPI · n8n · Docker
You get clean, documented, production-ready code fully yours.
Message me before ordering with what you're building I'll tell you honestly if it's a strong fit.
Get to know Rohma T
Rohma T
I will build intelligent AI Agents using LangChain, LangGraph, and RAG
- FromPakistan
- Member sinceAug 2023
Languages
Urdu, English
I build intelligent AI agents, RAG chatbots, and backend systems using Python (FastAPI, Django), AWS (SageMaker, Lambda), and GenAI frameworks. I specialize in creating scalable, memory-driven AI workflows that reason and respond like humans. Let’s bring your AI ideas to life with production-ready, efficient, and cloud-integrated solutions. 🚀
My Portfolio
Other AI Development Services I Offer
FAQ
What's the difference between a RAG chatbot and a normal chatbot?
A normal chatbot invents plausible answers. My RAG systems retrieve from your real documents using vector databases (Pinecone, Chroma, FAISS), cite every source, and say "I don't know" instead of guessing.
Can you connect the AI agent to my existing tools — CRM, APIs, spreadsheets?
Yes. I connect agents to HubSpot, Salesforce, Slack, Google Sheets, Shopify, and internal APIs using LangChain tool calling and n8n/Make/Zapier automations.
Why LangChain and LangGraph specifically?
LangGraph gives stateful, controllable agent workflows (branching, retries, human approval). LangChain handles prompts, retrieval, embeddings, and model integrations. Together they're the industry standard for production agents.
Is my data safe?
Yes. Everything can be deployed on your own cloud or run fully offline with local LLMs (Llama, Mistral, Ollama) — your data never leaves your control.
Do I get the source code?
Always. Clean, documented, production-ready code with a README covering setup and deployment.
Which LLMs do you support?
OpenAI GPT-4, Anthropic Claude, Google Gemini, Mistral, Llama, and local/open-source models.
What is a multi agent system and when do I need one?
Instead of one agent doing everything, a multi agent system uses specialized agents (e.g. researcher + writer + critic) coordinated by LangGraph. It's the right choice for complex workflows — research pipelines, content production, data analysis — where single agents lose track.
Can you run everything privately, without OpenAI?
Yes. I build fully private RAG systems and agents with local LLMs (Llama, Mistral) via Ollama or vLLM on your own hardware or cloud — no data ever leaves your environment.
