You will get a custom document layout analysis system with AI
Rising Talent
Rising Talent
Project details
I will build a custom AI-powered document layout analysis system tailored to your specific document types. Using state-of-the-art computer vision models (LayoutLM, Detectron2, YOLO), I automatically detect and extract text blocks, tables, figures, headers, and other structural elements from PDFs and images.
Whether you need to process invoices, contracts, scientific papers, or forms, I deliver a production-ready solution with API endpoint, documentation, and deployment support. All code is clean, tested, and well-documented.
Tech stack: Python, PyTorch, OpenCV, Tesseract OCR, LayoutLM
Whether you need to process invoices, contracts, scientific papers, or forms, I deliver a production-ready solution with API endpoint, documentation, and deployment support. All code is clean, tested, and well-documented.
Tech stack: Python, PyTorch, OpenCV, Tesseract OCR, LayoutLM
Machine Learning Tools
BERT, NumPy, OpenCV, pandas, Python Scikit-Learn, PyTorch, TensorFlow, Tesseract OCRWhat's included
| Service Tiers |
Starter
$300
|
Standard
$600
|
Advanced
$1,200
|
|---|---|---|---|
| Delivery Time | 7 days | 14 days | 21 days |
Number of Revisions | 1 | 3 | 5 |
Number of Model Variations | 1 | 2 | 3 |
Model Validation/Testing | |||
Model Documentation | - | ||
Data Source Connectivity | - | - | |
Source Code |
Frequently asked questions
About Mohammed
AI/ML Engineer
Nanterre, France - 10:48 am local time
𝗪𝗵𝗮𝘁 𝗜 𝗗𝗼:
* LLM & RAG Systems
- Document Q&A pipelines with minimal hallucination
- Text-to-SQL for business analytics
- Email automation using Generative AI
- LLM fine-tuning (LoRA, QLoRA)
* Computer Vision & Document AI
- Document Layout Analysis & OCR pipelines
- Information extraction from research papers
- Custom model training for domain-specific documents
* MLOps & Production
- Clean, tested code (90%+ coverage)
- FastAPI endpoints & Docker deployment
- End-to-end pipeline design
𝗧𝗲𝗰𝗵 𝗦𝘁𝗮𝗰𝗸:
Python, PyTorch, HuggingFace, LangChain, Transformers, FastAPI, Docker, PostgreSQL, Databricks, PySpark
𝗠𝗼𝗱𝗲𝗹𝘀:
GPT, Claude, Mistral, Llama, PaddleOCR, EasyOCR, YOLO
𝗪𝗵𝘆 𝗪𝗼𝗿𝗸 𝗪𝗶𝘁𝗵 𝗠𝗲:
- Production-ready code with full documentation
- Clear communication and fast delivery
- Experience with real-world business problems
Let's discuss your AI project.
Steps for completing your project
After purchasing the project, send requirements so Mohammed can start the project.
Delivery time starts when Mohammed receives requirements from you.
Mohammed works on your project following the steps below.
Revisions may occur after the delivery date.
Analyze sample documents and define extraction requirements
Review your sample documents, identify layout patterns, and confirm what elements need to be extracted (tables, text, figures). Define output format and success criteria.
Build and train custom layout detection model
Develop the AI model using PyTorch and fine-tune on your document type. Test detection accuracy on sample documents.