1

Document Analysis: We analyze your documents to understand structure, data fields, variations, and extraction requirements to design the optimal solution.

2

Model Development: Create custom extraction models using AI, NLP, and computer vision tailored to your specific document types and data fields.

3

Training & Validation: Train models on your document samples, validate accuracy across edge cases, and fine-tune for optimal performance.

4

Integration & Deployment: Seamlessly integrate extraction APIs into your workflows, implement automation triggers, and deploy to production with monitoring.

5

Transformation & Integration: Transform extracted data into your desired format, map fields to target schema, and integrate seamlessly with your existing systems and databases.

6

Monitoring & Optimization: Continuously monitor extraction pipelines, track accuracy metrics, handle errors automatically, and optimize performance for maximum efficiency.

🎯 High Accuracy

Industry-leading accuracy powered by AWS's continuously improving machine learning models trained on millions of diverse documents.

🎯 99%+ Accuracy Rate

Advanced AI and machine learning algorithms ensure high extraction accuracy with continuous learning and improvement from your specific data patterns.

💰 Cost Reduction

Eliminate manual data entry costs, reduce errors, and free up staff for higher-value tasks. Typical ROI achieved within 3-6 months of implementation.

🔒 Enterprise Security

Built on AWS infrastructure with encryption at rest and in transit, VPC support, and compliance certifications including HIPAA, GDPR, and SOC.

🔒 Secure & Compliant

Enterprise-grade security with encryption, access controls, audit trails, and compliance with GDPR, HIPAA, SOC 2, and industry-specific regulations.

🔄 Seamless Integration

Easy integration with your existing systems including CRM, ERP, databases, cloud storage, and business applications through APIs and connectors.

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.