You will get get a Custom AI Document Intelligence & RAG System
Project details
You will get a custom AI Document Intelligence & RAG system that allows users to ask questions about their own documents and receive relevant AI-generated answers based on the provided knowledge base.
I will build the complete pipeline from document processing and text extraction to chunking, embeddings, vector search, retrieval, LLM response generation, testing, and API integration where required.
The solution can be designed for business documents, technical documentation, manuals, reports, policies, research material, knowledge bases, and other supported document collections.
Depending on your requirements, the system can include semantic search, document-based question answering, source-aware responses, retrieval optimization, and a Python/API integration layer.
You will receive a professionally structured implementation with applicable source code, configuration, testing, and documentation. I focus on building practical RAG systems that are maintainable and suitable for real-world AI applications.
I will build the complete pipeline from document processing and text extraction to chunking, embeddings, vector search, retrieval, LLM response generation, testing, and API integration where required.
The solution can be designed for business documents, technical documentation, manuals, reports, policies, research material, knowledge bases, and other supported document collections.
Depending on your requirements, the system can include semantic search, document-based question answering, source-aware responses, retrieval optimization, and a Python/API integration layer.
You will receive a professionally structured implementation with applicable source code, configuration, testing, and documentation. I focus on building practical RAG systems that are maintainable and suitable for real-world AI applications.
Machine Learning Tools
BERT, ChatGPT, GPT-3, Keras, MLflow, NumPy, Open Neural Network Exchange, OpenCV, pandas, Python, Python Scikit-Learn, PyTorch, scikit-learn, SQL, TensorFlowWhat's included
| Service Tiers |
Starter
$75
|
Standard
$150
|
Advanced
$250
|
|---|---|---|---|
| Delivery Time | 3 days | 5 days | 7 days |
Number of Revisions | 1 | 2 | 3 |
Number of Model Variations | 1 | 2 | 3 |
Number of Scenarios | 1 | 4 | 6 |
Number of Graphs/Charts | 1 | 2 | 3 |
Model Validation/Testing | |||
Model Documentation | |||
Data Source Connectivity | |||
Source Code |
Frequently asked questions
About M Asad
Machine Learning Engineer | AI, LLM, RAG & Computer Vision
Lahore, Pakistan - 12:33 pm local time
I’m a Machine Learning Engineer and Python Developer specializing in building practical AI and machine learning solutions from model development to API and application integration.
My core expertise includes:
• Machine Learning & Deep Learning
• Python, TensorFlow, Keras & Scikit-Learn
• LLM Applications, RAG & AI Agents
• LangChain & LangGraph
• Vector Databases — FAISS, Chroma & Qdrant
• NLP & AI Chatbots
• Computer Vision, OpenCV & YOLO
• FastAPI & REST APIs
• Predictive Analytics & Data Analysis
• React, Streamlit, Docker & Git/GitHub
I have professional experience designing and deploying ML services across NLP, computer vision, and predictive analytics. I’ve also built FastAPI-based REST APIs for ML models and integrated AI features into web applications.
My project experience includes an LLM-powered RAG assistant with agentic workflows, an agriculture AI assistant with English/Urdu chatbot support, a multimodal emotion-based recommendation system, a real-time fire detection system, and a YOLO-based object detection application.
I focus on building solutions that are practical, reliable, and ready to move beyond a basic prototype.
If you need help with an AI/ML model, RAG application, AI agent, computer vision system, predictive analytics solution, or FastAPI ML backend, I’d be happy to help.
Let’s turn your AI idea into a working solution.
Steps for completing your project
After purchasing the project, send requirements so M Asad can start the project.
Delivery time starts when M Asad receives requirements from you.
M Asad works on your project following the steps below.
Revisions may occur after the delivery date.
Document & Requirement Analysis
I will review your documents, requirements, data format, expected questions, and target application environment.
Document Processing & Chunking
I will extract, clean, structure, and chunk the document content to enable efficient retrieval.