You will get AI Document Q&A System | Chat with PDFs using GPT
Project details
You will get an AI-powered document intelligence system that allows users to upload PDFs or documents and ask questions about the content in natural language.
This system uses Retrieval Augmented Generation (RAG) with embeddings and vector search to find the most relevant information from your documents before generating accurate responses using a Large Language Model.
Unlike basic chatbots, this solution understands document context and retrieves precise answers from your knowledge base. It is ideal for businesses that want to analyze large documents, automate knowledge retrieval, and improve productivity.
The platform can support multiple documents, semantic search, and contextual Q&A, making it useful for research, internal knowledge bases, legal documents, technical documentation, and customer support.
Key Features
• Upload and analyze PDF / DOC documents
• Semantic document search using embeddings
• Context-aware Q&A with AI
• Retrieval-Augmented Generation pipeline
• Simple web interface for document querying
If you want a powerful AI system to chat with your documents and extract information instantly, this project is designed to deliver a scalable and reliable solution.
This system uses Retrieval Augmented Generation (RAG) with embeddings and vector search to find the most relevant information from your documents before generating accurate responses using a Large Language Model.
Unlike basic chatbots, this solution understands document context and retrieves precise answers from your knowledge base. It is ideal for businesses that want to analyze large documents, automate knowledge retrieval, and improve productivity.
The platform can support multiple documents, semantic search, and contextual Q&A, making it useful for research, internal knowledge bases, legal documents, technical documentation, and customer support.
Key Features
• Upload and analyze PDF / DOC documents
• Semantic document search using embeddings
• Context-aware Q&A with AI
• Retrieval-Augmented Generation pipeline
• Simple web interface for document querying
If you want a powerful AI system to chat with your documents and extract information instantly, this project is designed to deliver a scalable and reliable solution.
AI Algorithms
Feedforward Neural Network, Large Language Model, Multilayer Perceptron, Recurrent Neural Network, Transformer ModelAI Applications
AI Chatbot, AI Content Creation, AI-Enhanced Classification, AI-Generated Code, Conversational AI, Image Processing, Machine Translation, Natural Language Generation, Natural Language Understanding, Sentiment Analysis, Sequence Modeling, Text RecognitionAI Development Language
PythonAI Tools
Azure OpenAI, GitHub Copilot, Gradio, Hugging Face, PyTorch, Replit, Streamlit, TensorFlowAI Models
BLOOM, ChatGPT, GPT-3, GPT-4, GPT-J, GPT-Neo, LLaMA, OpenAI Codex, WhisperWhat's included
| Service Tiers |
Starter
$25
|
Standard
$60
|
Advanced
$120
|
|---|---|---|---|
| Delivery Time | 3 days | 4 days | 7 days |
Number of Revisions | 1 | 2 | 0 |
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
+$24 - $120
Additional Revision
+$5
Website Integration
(+ 2 Days)
+$30
Vector Database Setup (Pinecone/FAISS)
(+ 2 Days)
+$20
UI Dashboard (Streamlit)
(+ 1 Day)
+$35Frequently asked questions
About Mohammad Abdur Rehman
SaaS | AI Models | AI Apps | AI, SaaS, Python Expert
Lahore Cantt, Pakistan - 12:31 am local time
I'm Abdur Rehman, a Full-Stack AI Engineer and CTO specializing in production-ready AI SaaS platforms, RAG systems, and autonomous AI agents. I've shipped an AI fitness coach with real-time computer vision feedback, an AI exam generator that creates quizzes automatically from course syllabi, and an architecture intelligence system that analyzes entire codebases and generates risk-aware engineering decisions.
I don't build prototypes. I build systems that scale.
What I bring to your AI project:
I design and deploy RAG pipelines using LangChain, OpenAI, and vector databases so your AI retrieves accurate contextual information instead of hallucinating. I build AI agents with autonomous decision-making workflows that handle real business logic end to end. I architect FastAPI backends that are clean, scalable, and production-ready from the first deployment. I integrate LLMs into SaaS platforms with proper authentication, billing, and dashboards so you have a complete product, not just an AI feature. I handle LLM evaluation, testing, and optimization so your system performs reliably under real usage.
IBM is certified in RAG and Agentic AI. Google Cloud certified. Top 4 nationally in Google Code Jam 2021.
If you're building an AI product and need someone who thinks about reliability, scalability, and user impact before writing the first line of code, let's talk.
What are you building?
Steps for completing your project
After purchasing the project, send requirements so Mohammad Abdur Rehman can start the project.
Delivery time starts when Mohammad Abdur Rehman receives requirements from you.
Mohammad Abdur Rehman works on your project following the steps below.
Revisions may occur after the delivery date.
Requirement analysis
Review your documents and understand how the AI system should retrieve and answer questions from the content.
Document processing
Convert uploaded documents into embeddings and store them in a vector database for semantic search.