I will develop custom ai agents, rag pipelines and llm automation


About this gig
PLEASE MESSAGE ME BEFORE ORDERING!
Looking for an AI system that truly understands your data and automates workflows?
Unlike freelancers who build "generic ChatGPT wrappers," I engineer production-ready RAG Systems and Custom AI Agents focused on real business use cases.
What I Build:
- Enterprise RAG Pipelines: Securely chat with your PDFs, databases, or knowledge base with zero hallucinations.
- Autonomous AI Agents: Multi-agent LangChain workflows that process data and execute complex tasks 24/7.
- Local LLM Deployments: Privacy-first AI using open-source models (Llama 3) for sensitive data.
- API Integrations: Seamlessly connecting AI to your SaaS & CRMs.
Why Choose Me? I am a professional Machine Learning Engineer and an AWS Certified AI Practitioner. I don't just write basic prompts; I recently won an innovation award for architecting a high-accuracy Legal RAG pipeline using Hugging Face and Llama 3.
️ Tech Stack: Python, LangChain, GPT, Llama, FastAPI, Docker, Vector DBs (Pinecone, Chroma).
Message me today to discuss your project!
Get to know Sankalp S
AI Engineer Intern
- FromIndia
- Member sinceApr 2026
Languages
Hindi, English
FAQ
My data is highly sensitive. Can we keep it private?
Absolutely. I can build Local RAG systems using open-source models like Llama 3. This ensures your proprietary data never leaves your server or touches public APIs.
What is the difference between a standard Chatbot and the "AI Agents" you offer?
A standard chatbot just answers questions. The AI Agents I build can actually act. They can browse the web, query your databases, and update your CRM autonomously, effectively acting as a digital employee.
Can the AI agent be trained on my specific company documents?
Yes. I build specialized RAG (Retrieval-Augmented Generation) systems. This means the AI will reason and answer questions based strictly on your uploaded PDFs, Notion docs, or databases, preventing "hallucinations."Yes. I build specialized RAG (Retrieval-Augmented Generation) systems. This means the

