Agentic Document Extraction: Automating Data Processing in the Hydrocarbon Industry
%
Reduction in Manual Processing Time
%
Increased Data Accuracy
%
Automation of End-to-End Workflow
Improved Traceability and Auditability
Thanks to real-time logs and validation tracking, every correction and approval could be traced, which improved compliance and model refinement.
Scalable Across Document Types
The hybrid AI models handled both two-page and three-page variations, vendor-specific layouts, and even low-quality scans—making the system scalable across document formats and vendors.
Project Overview
A leading company in the hydrocarbon industry faced a critical challenge: manually extracting and structuring data from industry-specific documents. Initially, employees had to read and manually enter data from chemical reports, which was time-consuming and error-prone. The client sought an automated solution—a dashboard that allows users to upload scanned documents or images, extract relevant information into structured fields, and provide a verification mechanism for manual corrections before storing the data in a database.
Key Challenges
Every website was different, and here’s what made the project both exciting and challenging:
Document Variability
While most documents were two pages long, occasional three-page documents caused processing inconsistencies in the system.
Complex Formatting
Different vendors and sources provided documents in varying layouts, fonts, and structures, making uniform extraction difficult.
Handwritten and Low-Quality Scans
Some reports included handwritten notes or were of poor quality, making text extraction challenging.
Domain-Specific Terminology
Chemical industry reports contained specialized terminology, requiring fine-tuning of models for accurate extraction.
Validation and Correction
The client needed an interactive validation step where extracted data could be reviewed, corrected if necessary, and confirmed before being stored.
Our Approach
Deep Learning-Based OCR and Computer Vision
- We utilized Tesseract OCR and Google Vision API to extract text from scanned documents.
- A custom-trained deep learning model (based on Transformer architectures like LayoutLM) improved extraction accuracy by learning from structured and unstructured document layouts.
- Fine-tuned image pre-processing techniques (such as noise reduction and adaptive thresholding) improved OCR accuracy for low-quality scans.
Generative AI for Context-Aware Data Extraction
- LLMs (like GPT-4 and BERT) were integrated to refine extracted text by understanding the chemical context and correcting OCR misinterpretations.
- Few-shot learning techniques were applied to enhance the AI model’s ability to extract structured information across varied document formats.
- An AI-powered validation assistant suggested probable corrections based on extracted data patterns.
Vision-Based AI Agent for Intelligent Parsing
- A Computer Vision model (based on YOLO/Detectron2) was implemented to recognize tables, section headers, and handwritten content separately.
- Custom bounding box detection and segmentation techniques helped identify key-value pairs in complex document layouts.
- The system automatically highlighted discrepancies for manual verification, reducing human effort significantly.
Interactive Dashboard for User Verification
- A React-based user interface was built, enabling clients to:
– Upload documents/images.
– View extracted data in structured fields.
– Edit and correct any misinterpretations.
– Approve and save data to the database. - Audit logs were implemented to track manual corrections for continuous model improvements.
Technologies
TensorFlow and PyTorch
Tesseract OCR
Google Vision API
Conclusion
By integrating deep learning, generative AI, and computer vision, we built an intelligent document extraction system tailored for the hydrocarbon industry. The solution reduced manual effort, improved data accuracy, and enabled rapid validation and correction, resulting in an efficient and scalable approach for document processing. This AI-powered agentic system not only streamlined operations but also positioned the client at the forefront of digital transformation in data extraction and processing.