You will get AI Document Data Extraction
Project details
What makes my approach different:
• VISION AI, NOT JUST OCR. I use modern vision language models that "see" your document as a whole — layout, tables, handwriting, mixed formats. This works where traditional OCR breaks down: messy scans, handwritten fields, complex table structures.
• DUAL-MODEL CROSS-CHECK. Every extraction is independently verified by a second AI model from a different family. When the two models disagree on a field, the system flags it for human review instead of silently passing a wrong value. This catches the most dangerous error in document AI: confident-looking but incorrect data.
• HONEST, NOT PERFECT. The system tells you what it could not read, rather than guessing. Missing fields are flagged. Disputed fields show both readings. You review only the flagged items — not every field.
• PRIVACY-READY. Everything can run on your own infrastructure — no data leaves your network. Useful for confidential documents (contracts, financials, HR records). Cloud deployment is also available if you prefer.
• VISION AI, NOT JUST OCR. I use modern vision language models that "see" your document as a whole — layout, tables, handwriting, mixed formats. This works where traditional OCR breaks down: messy scans, handwritten fields, complex table structures.
• DUAL-MODEL CROSS-CHECK. Every extraction is independently verified by a second AI model from a different family. When the two models disagree on a field, the system flags it for human review instead of silently passing a wrong value. This catches the most dangerous error in document AI: confident-looking but incorrect data.
• HONEST, NOT PERFECT. The system tells you what it could not read, rather than guessing. Missing fields are flagged. Disputed fields show both readings. You review only the flagged items — not every field.
• PRIVACY-READY. Everything can run on your own infrastructure — no data leaves your network. Useful for confidential documents (contracts, financials, HR records). Cloud deployment is also available if you prefer.
Machine Learning Tools
Microsoft Excel, NumPy, pandas, Python, PyTorch, Tesseract OCRWhat's included $800
These options are included with the project scope.
$800
- Delivery Time 14 days
- Number of Revisions 2
- Number of Model Variations 2
- Number of Scenarios 1
- Number of Graphs/Charts 0
- Model Validation/Testing
- Model Documentation
- Source Code
Optional add-ons
You can add these on the next page.
On-Server Deployment & Setup
(+ 3 Days)
+$400About Merve
AI Document Processing & RAG Engineer - PDF to Structured Data
Izmir, Turkey - 9:58 pm local time
What makes my approach different:
• VISION AI, NOT JUST OCR. I use modern vision language models that "see" your document as a whole — layout, tables, handwriting, mixed formats. This works where traditional OCR breaks down: messy scans, handwritten fields, complex table structures.
• DUAL-MODEL CROSS-CHECK. Every extraction is independently verified by a second AI model from a different family. When the two models disagree on a field, the system flags it for human review instead of silently passing a wrong value. This catches the most dangerous error in document AI: confident-looking but incorrect data.
• HONEST, NOT PERFECT. The system tells you what it could not read, rather than guessing. Missing fields are flagged. Disputed fields show both readings. You review only the flagged items — not every field.
• PRIVACY-READY. Everything can run on your own infrastructure — no data leaves your network. Useful for confidential documents (contracts, financials, HR records). Cloud deployment is also available if you prefer.
I also build RAG systems (document Q&A): upload your documents, ask questions in plain language, get answers with source citations. Same privacy options, same honest "I don't know" when the answer isn't there.
Typical projects:
Document extraction: → Extract data from 500 invoices into one Excel spreadsheet → Pull party names, dates, and amounts from scanned contracts → Process application forms and deliver structured data in Excel
Document Q&A (RAG): → Build a searchable assistant over internal policy documents.
Steps for completing your project
After purchasing the project, send requirements so Merve can start the project.
Delivery time starts when Merve receives requirements from you.
Merve works on your project following the steps below.
Revisions may occur after the delivery date.
Review sample documents & confirm extraction scope
Design extraction schema based on your document fields