Fintech Invoice Data Extraction
Background
A fintech company managing high-volume accounts payable operations engaged CalyzaTech to automate its invoice processing workflow. The organization processes hundreds of vendor invoices daily, each containing multi-page documents such as tax invoices, purchase orders, delivery challans, and GST-compliant records. Accurate and timely extraction of structured financial data is critical for vendor payments, GST compliance, and ERP integration.
Challenges
Manual extraction of invoice data consumed 15–20 minutes per invoice.
High risk of errors in GST details, tax calculations, PO numbers, and line items.
Multiple vendor invoice formats without standardized layouts.
Manual workflows could not scale during month-end and peak processing periods.
Slow invoice processing delayed vendor payments and financial reporting.
Limited auditability and compliance due to inconsistent manual processes.
Solution
CalyzaTech designed and deployed an AWS-native serverless invoice intelligence platform that automatically transforms multi-page invoices into structured, schema-validated JSON records.
The platform combines Amazon Textract for OCR-based text extraction with Amazon Bedrock (Amazon Nova Pro) for intelligent structured data extraction. The solution is orchestrated through a secure event-driven architecture with comprehensive monitoring and automated job tracking.
The automated workflow includes:
- Ingestion & Validation: Receives and validates invoice documents through secure APIs.
- Job Tracking: Generates a unique Job ID and tracks processing status throughout the workflow.
- Smart OCR Processing: Uses Amazon Textract to digitize invoices while leveraging Amazon S3 caching to reduce repeat OCR costs by up to 75%.
- Context Aggregation: Consolidates OCR output into a unified document with confidence scoring.
- Structured AI Extraction: Amazon Bedrock extracts and validates 40+ financial fields into standardized JSON.
- Storage & Handoff: Securely stores structured results in Amazon S3 for downstream ERP integration.
Architecture & Solution Design
The platform was implemented using a serverless-first and event-driven architecture with:
- Multi-AZ high availability
- Secure-by-design implementation
- Pay-per-use cost optimization
- Scalable cloud-native infrastructure
As invoice volumes increased, client faced serious operational and technical challenges.
AWS Services
The solution runs on a secure, serverless AWS architecture with encrypted storage, authentication, automated scaling, and full observability.
Outcomes
- Efficiency: Reduced invoice processing from 15–20 minutes to 45 seconds–2 minutes, significantly minimizing manual effort.
- Accuracy: Generated high-accuracy, schema-validated JSON across 40+ financial fields using Amazon Textract and Amazon Bedrock.
- Performance: Serverless architecture automatically scales to process hundreds of invoices concurrently.
- Observability: Real-time job tracking through AWS Systems Manager and AWS CloudWatch provides complete workflow visibility.
- Compliance: Encrypted Amazon S3 storage, IAM-based security, Cognito authentication, and comprehensive audit logging ensure secure data handling.
- Cost Optimization: Amazon S3 OCR caching reduces Amazon Textract processing costs by up to 75%, while AWS Lambda’s pay-per-use model minimizes infrastructure costs.