Intelligent Data Extraction Services
Oodles delivers AI-powered data extraction solutions that convert unstructured and semi-structured data into clean, structured, and actionable information. Our data extraction platforms are built using Python, OCR engines, natural language processing (NLP), computer vision, and machine learning to automate data capture at scale with high accuracy and enterprise-grade security.
What is Data Extraction?
Data extraction is the automated process of identifying, capturing, and structuring data from unstructured and semi-structured sources such as PDFs, scanned images, emails, forms, websites, and databases. Oodles uses Python-based OCR engines, NLP models, computer vision pipelines, and rule-based validation layers to extract accurate data while minimizing manual intervention and operational errors.
Key Data Extraction Capabilities
📄 Document Data Extraction
Extract structured data from invoices, receipts, contracts, forms, and reports using intelligent document processing workflows.
🔍 OCR Technology
Deep learning–based OCR engines extract printed and handwritten text from scanned documents and images with high accuracy.
🌐 Web Data Extraction
Automated data extraction from websites and portals using crawlers, parsers, and data normalization pipelines.
🤖 AI & NLP-Based Extraction
Machine learning and NLP models identify entities, fields, and contextual relationships to improve extraction accuracy over time.
⚡ Real-Time & API Processing
API-driven and event-based extraction pipelines enable near real-time document ingestion and processing.
🔒 Secure & Compliant
End-to-end security with encryption, access control, audit logs, and compliance with GDPR, HIPAA, and industry standards.
Our Data Extraction Methodology
A structured, scalable approach to accurate data extraction
1
Document Analysis: Analyze document layouts, data fields, and variations to define optimal extraction logic.
2
Model Development: Build extraction pipelines using Python, OCR engines, NLP models, and computer vision frameworks.
3
Training & Validation: Train and validate models on real document samples to handle edge cases and variations.
4
API Deployment: Deploy extraction services via REST APIs, queues, and automation workflows.
5
Data Transformation: Normalize and map extracted data to target schemas and business systems.
6
Monitoring & Optimization: Continuously monitor accuracy, throughput, and errors to improve extraction performance.
Why Why Choose Oodles for Data Extraction?
🎯 High Accuracy
Advanced OCR and AI models deliver consistent, high-precision data extraction.
🔒 Enterprise Security
Secure pipelines with encryption, access control, and regulatory compliance.
🔄 Seamless Integration
Easy integration with CRM, ERP, databases, and cloud platforms.
Data Extraction in Action
Automatically extract structured data from forms and tables using AI-driven document understanding and layout analysis.
Data Extraction Use Cases Across Industries
Discover how businesses leverage data extraction to streamline operations and gain competitive advantages
Financial Services - Invoice & Receipt Processing
Oodles builds automated invoice and receipt extraction systems that integrate with accounting platforms to reduce manual processing and errors.
Healthcare - Medical Records Digitization
Healthcare data extraction solutions developed by Oodles digitize medical records and lab reports while maintaining strict data security and compliance.
Legal - Contract Analysis & Review
Legal document extraction pipelines identify clauses, dates, and entities from contracts and case files for faster review and compliance.
Government - Form Processing & Citizen Services
Digitize government forms, applications, permits, and citizen documents for faster processing, improved service delivery, and reduced operational costs.
Enterprise - Document Management Systems
Build searchable document archives by extracting and indexing content from legacy documents, contracts, records, and business correspondence.
Logistics - Shipping Document Processing
Automate processing of bills of lading, customs forms, shipping manifests, and delivery receipts to streamline supply chain operations and reduce errors.
Types of Data Extraction Methods
Structured Data Extraction
Extract data from organized sources like databases, spreadsheets, CSV files, and APIs where information follows a predefined format and schema with clear fields and relationships.
Unstructured Data Extraction
Extract information from unorganized content like PDFs, emails, text documents, images, and scanned files using AI, NLP, and OCR technologies to identify and structure relevant data.
Semi-Structured Data Extraction
Process data with some organizational properties like XML, JSON, HTML, and log files that contain tags and hierarchies but don't fit traditional database structures.
FAQs (Frequently Asked Questions)
AI-powered data extraction services use OCR, natural language processing, and machine learning models to automatically extract structured and unstructured data from PDFs, scanned documents, invoices, and digital forms with high accuracy.
Intelligent data extraction solutions process invoices, contracts, bank statements, tax forms, insurance documents, healthcare records, and web content to convert raw information into structured datasets.
Data extraction software integrates through APIs, cloud services, and automation workflows to connect with CRM, ERP, databases, and analytics platforms for seamless and scalable data processing.
Yes, advanced data extraction platforms use Optical Character Recognition (OCR) and intelligent document processing to accurately capture printed text, handwritten content, tables, and key-value pairs.
Scalable data extraction systems support batch processing, real-time workflows, and cloud infrastructure to manage high document volumes securely and efficiently.
Accuracy is maintained through model training, validation pipelines, performance monitoring, human-in-the-loop review, and continuous AI optimization to ensure reliable extraction results.
AI data extraction reduces manual data entry, accelerates document workflows, improves compliance, enhances analytics readiness, and enables faster data-driven business decisions.
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