I will build ai agents with rag, langchain, langgraph, n8n and make


About this gig
AI Research Agent with RAG, LangChain, LangGraph, n8n & Make
This project focuses on developing an AI-powered research agent that can retrieve relevant information, answer questions using provided documents, perform research, and automate repetitive workflows.
The system combines Retrieval-Augmented Generation (RAG), Large Language Models (LLMs), and agent workflows to create a practical AI solution that goes beyond basic chatbot functionality.
Key Features:
- AI Agent Development: Intelligent research and task execution.
- RAG Implementation: Context-based answers from documents.
- LangChain & LangGraph: Structured AI workflows and tool integration.
- AI Integration: Connects LLMs and supported APIs.
- Workflow Automation: Uses n8n and Make to automate repetitive tasks.
️ Tech Stack: Python, FastAPI, Streamlit, LangChain, LangGraph, RAG, vector databases, LLM APIs, n8n, and Make.
Use Cases
- Research and information summarization
- Document question-answering systems
- Internal knowledge assistants
- Business information retrieval
- AI-powered workflow automation
- Research reporting and productivity tools
Have an AI project in mind? Message me to discuss your requirements! .
Get to know Devasath Anand
AIML Engineer, Data Science, Web Developer
- FromIndia
- Member sinceOct 2026
- Avg. response time1 hour
Languages
Hindi, Telugu, English
FAQ
What types of AI solutions do you develop?
I develop custom AI agents, RAG-powered chatbots, document question-answering systems, AI research assistants, and intelligent workflow automation solutions tailored to your business needs.
Can you integrate AI with my existing business applications?
Yes. I can integrate AI models and supported APIs into existing applications and connect workflows using n8n or Make, depending on your requirements and the availability of integrations.
How do you ensure the AI provides relevant and reliable answers?
For RAG-based solutions, I configure document retrieval to provide relevant context to the AI model. Source references and fallback responses can be implemented where appropriate to help reduce unsupported answers.
What information is required before placing an order?
Please share your project objectives, required features, preferred integrations, and any relevant documents or technical requirements. I'll review the scope and recommend a suitable approach before we begin.
My documents are confidential. Is that safe?
Yes. Your data stays in your environment, and I can deploy the entire system on your own cloud account or infrastructure so nothing leaves your control.

