You will get a custom Python OCR pipeline for unstructured document parsing
Project details
Corporate operations are heavily paralyzed by the sheer volume of unstructured physical documents, companies waste millions of dollars paying humans to manually read scanned invoices, legal contracts, and messy PDFs just to type that data into a CRM, relying on basic PDF readers or cheap OCR software is useless because the moment a supplier changes their invoice layout by one millimeter the entire extraction breaks
I engineer resilient Python computer vision pipelines that do not rely on fragile static templates, we build intelligent architectures using spatial bounding boxes and natural language processing to actually understand the context of the document, whether you need to ingest a backlog of fifty thousand scanned receipts or automate your daily accounts payable workflow directly from an email inbox, i build the localized backend to handle it, we digitize the chaos, apply noise reduction filters to bad scans, and output perfectly structured JSON payloads directly into your database.
I engineer resilient Python computer vision pipelines that do not rely on fragile static templates, we build intelligent architectures using spatial bounding boxes and natural language processing to actually understand the context of the document, whether you need to ingest a backlog of fifty thousand scanned receipts or automate your daily accounts payable workflow directly from an email inbox, i build the localized backend to handle it, we digitize the chaos, apply noise reduction filters to bad scans, and output perfectly structured JSON payloads directly into your database.
Programming Languages
Python, Java, C#Coding Expertise
Performance Optimization, SecurityWhat's included
| Service Tiers |
Starter
$450
|
Standard
$1,400
|
Advanced
$3,200
|
|---|---|---|---|
| Delivery Time | 5 days | 14 days | 25 days |
Number of Revisions | 1 | 2 | 3 |
Install Script | - | ||
Test Script | |||
Task Automation | - | - |
Frequently asked questions
About Eduardo
Senior Anti-Bot Automation Engineer & Quant Developer (Python/C++)
Divinopolis, Brazil - 1:52 pm local time
I am a Systems Engineer specialized in high-level automation and quantitative trading. I don't just write scripts. I build resilient, stealthy, and industrial-grade architectures. When it comes to anti-bot bypass and enterprise web extraction, I engineer custom headless browser stealth using Playwright, Puppeteer, and Selenium. I routinely reverse-engineer WebGL, Canvas, and WebRTC fingerprints. To bypass strict Datadome, PerimeterX, or Akamai checks, I deploy kernel-level hardware injection like virtual V4L2loopback devices. This allows complex DOM parsing and CAPTCHA circumvention for massive B2B data pipelines.
On the financial engineering side, I develop fail-safe Expert Advisors using C++ for MT4 and MT5. My algorithmic trading architectures rely heavily on Smart Money Concepts. I map liquidity sweeps, order blocks, and multi-timeframe price action entirely without lagging indicators. I also implement stealth trade management to hide stop losses and take profits from brokers, preventing virtual stop-outs. This includes real-time WebSockets integration and OS-level memory reading for dynamic web brokers. I only take on complex, high-value challenges. If your current bot is getting blocked or if you need a bulletproof financial engine ready to protect real capital, let's discuss your target and scale.
"At 6, I disassembled toys to understand their mechanics, by 12, I was captivated by the intersection of art and mathematics. I see the micro and macro connections like a musical arrangement, to me, everything is a grand opera; a harmony that makes my eyes shine."
Steps for completing your project
After purchasing the project, send requirements so Eduardo can start the project.
Delivery time starts when Eduardo receives requirements from you.
Eduardo works on your project following the steps below.
Revisions may occur after the delivery date.
Layout Profiling and Computer Vision Setup
I analyze your sample documents to configure the appropriate OpenCV noise reduction filters ensuring the optical engine can read even the most degraded scans.
Core Parsing Logic Engineering
I write the Python architecture to identify key-value pairs dynamically so the script finds the correct data even if the physical layout of the document shifts unexpectedly.