You will get RAG readiness audit for your PDF knowledge base


Project details
I will assess whether your PDF document collection is ready to support a reliable RAG or document-based AI assistant.
I will extract and index up to 10 PDFs, create a 20-question benchmark, and test retrieval relevance, citation quality, missing-information handling, and unsupported-answer risk.
You will receive a client-ready audit report containing:
• Retrieval and citation results
• Answerable and unanswerable question tests
• Examples of successful and failed responses
• Identified knowledge-base gaps
• Prioritized recommendations for improving your future RAG or PDF chatbot
This project evaluates the document knowledge base itself. It does not include deployment of a production chatbot or testing of an existing live application.
I will extract and index up to 10 PDFs, create a 20-question benchmark, and test retrieval relevance, citation quality, missing-information handling, and unsupported-answer risk.
You will receive a client-ready audit report containing:
• Retrieval and citation results
• Answerable and unanswerable question tests
• Examples of successful and failed responses
• Identified knowledge-base gaps
• Prioritized recommendations for improving your future RAG or PDF chatbot
This project evaluates the document knowledge base itself. It does not include deployment of a production chatbot or testing of an existing live application.
AI Algorithms
Large Language Model, Transformer ModelAI Applications
AI Chatbot, Conversational AI, Natural Language Generation, Natural Language UnderstandingAI Development Language
PythonAI Tools
Hugging Face, PyTorchAI Models
BERTWhat's included $99
These options are included with the project scope.
$99
- Delivery Time 3 days
- Number of Revisions 1
- Model Documentation
- Model Testing & Optimization
- Natural Language Processing
Frequently asked questions
About Marouan
Python Automation & AI Agent Developer | Data Extraction & APIs
Larache, Morocco - 7:18 am local time
I build practical solutions that turn repetitive or complex tasks into reliable automated workflows. My experience includes developing LLM-based multi-agent systems, RAG applications, web and PDF data-extraction pipelines, backend APIs, and full-stack applications.
I can help with:
• Python automation and custom scripts
• AI agents and multi-agent workflows
• LLM and RAG application development
• Web scraping and structured data extraction
• PDF, Excel, and CSV processing
• API development and integration
• Data cleaning, transformation, and ETL
• Backend development with Python or Spring Boot
My technical background includes Python, Java, FastAPI, Spring Boot, Angular, PostgreSQL, Docker, Kubernetes, machine learning, and large language models.
I focus on clear requirements, clean implementation, thorough testing, and dependable delivery. Whether you need a small automation script, a data-processing workflow, or an AI-powered prototype, I aim to provide a solution that is practical, maintainable, and aligned with your exact needs.
Steps for completing your project
After purchasing the project, send requirements so Marouan can start the project.
Delivery time starts when Marouan receives requirements from you.
Marouan works on your project following the steps below.
Revisions may occur after the delivery date.
Document review and benchmark design
I review the submitted PDFs, intended use case, and priority questions.
Knowledge-base indexing and testing
I extract, chunk, and index the documents, then run the 20-question benchmark.