You will get RAG based document analysis system using LangChain and OpenAI/gemini/groq
Project details
I build RAG systems that actually work in production — not just demos that fall apart when you upload a real document. Every project I deliver is built the same way I built AgriMind: clean pipeline, structured output, and fully deployed code you can run and maintain yourself.
Here's what makes my approach different from most RAG freelancers on Upwork:
Most developers will connect LangChain to OpenAI, wrap it in a basic UI, and call it done. That works for simple Q&A. But if you need the system to follow a fixed reasoning sequence, enforce a specific output structure, handle multilingual input, or scale to multiple users — that requires proper architecture decisions from day one. Chunking strategy, embedding model selection, retrieval tuning, prompt design, and output schema enforcement all matter and I handle all of them.
I also don't disappear after delivery. I include documentation, a setup file, and clear handover notes so you're never dependent on me to keep the system running.
If you're not sure whether your use case is a good fit, message me before ordering. I'd rather spend 5 minutes answering your question than have either of us waste time on a mismatched project.
Here's what makes my approach different from most RAG freelancers on Upwork:
Most developers will connect LangChain to OpenAI, wrap it in a basic UI, and call it done. That works for simple Q&A. But if you need the system to follow a fixed reasoning sequence, enforce a specific output structure, handle multilingual input, or scale to multiple users — that requires proper architecture decisions from day one. Chunking strategy, embedding model selection, retrieval tuning, prompt design, and output schema enforcement all matter and I handle all of them.
I also don't disappear after delivery. I include documentation, a setup file, and clear handover notes so you're never dependent on me to keep the system running.
If you're not sure whether your use case is a good fit, message me before ordering. I'd rather spend 5 minutes answering your question than have either of us waste time on a mismatched project.
AI Algorithms
Convolutional Neural Network, Feedforward Neural Network, Gated Recurrent Unit, Generative Adversarial Network, Large Language Model, Long Short-Term Memory Network, Multimodal Large Language Model, Recurrent Neural Network, Transformer Model, Variational AutoencoderAI Applications
AI Chatbot, AI-Enhanced Classification, Conversational AI, Natural Language Generation, Natural Language Understanding, Sentiment AnalysisAI Development Language
PythonAI Tools
Azure OpenAI, GitHub Copilot, Hugging Face, Microsoft CNTK, PyTorch, Streamlit, TensorFlow, Word2vecAI Models
BERT, ChatGPT, GPT-3, GPT-4, LLaMA, Stable DiffusionWhat's included
| Service Tiers |
Starter
$299
|
Standard
$599
|
Advanced
$999
|
|---|---|---|---|
| Delivery Time | 4 days | 7 days | 14 days |
Number of Revisions | 1 | 2 | 2 |
AI Model Integration | |||
Batch Normalization | - | - | |
Database Integration | - | ||
Detailed Code Comments | |||
Image Upscaling | - | ||
MLOps | - | - | |
Model Deployment | - | ||
Model Documentation | - | ||
Model Monitoring | - | - | |
Model Testing & Optimization | - | ||
Model Tuning | - | ||
Natural Language Processing | |||
NLP Tokenization | - | ||
Pre-Training | - | ||
Prompt Engineering | |||
Setup File | |||
Source Code |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$75 - $350
Additional Revision
+$100Frequently asked questions
About Muhammad
AI Engineer | RAG Systems & Computer Vision
Karachi, Pakistan - 1:37 am local time
My work sits at the intersection of applied deep learning and production engineering. I've built and deployed RAG pipelines using LangChain and OpenAI, developed brain tumor segmentation systems on multi-modal MRI data, implemented Vision Transformer architectures from scratch, and contributed to a confidential intraoperative AI guidance system for surgical support. My research was published in AgriEngineering (MDPI, 2026) as first author, and I was selected as a Global Top 5 Finalist at IEEE YESIST12 in Kuala Lumpur.
I don't just train models — I build systems. That means clean APIs with FastAPI, containerized deployments with Docker, experiment tracking with MLflow, and code that someone else can actually maintain after I hand it over.
If you're building something in RAG, medical imaging, agentic AI, or computer vision — let's talk.
Steps for completing your project
After purchasing the project, send requirements so Muhammad can start the project.
Delivery time starts when Muhammad receives requirements from you.
Muhammad works on your project following the steps below.
Revisions may occur after the delivery date.
Document Ingestion & Setup
I'll parse your PDF, clean and chunk the text, generate embeddings, and store them in a vector database ready for retrieval.
RAG Pipeline Developmen
I'll build the retrieval chain using LangChain and OpenAI, connecting your vector store to a structured prompt that enforces your required output format