Growing Invoice Volumes Were Overloading Manual Finance Workflows

Manual invoice processing required finance teams to read documents, enter financial information, verify tax details, and track each invoice across multiple systems. Differences in document formats, layouts, page counts, and handwriting made consistent data extraction difficult.

• Reduce repetitive invoice data entry and manual verification.
• Process scanned, digital, multi-page, and handwritten invoices.
• Convert inconsistent invoice formats into a standard data structure.
• Validate GST information and other required financial fields.
• Track invoices and processing status in real time.
• Scale monthly capacity without introducing fixed infrastructure costs.

From Manual Invoice Entry to Serverless Financial Automation

Invoice Workflow Discovery

We mapped how invoices were received, reviewed, validated, stored, and transferred into financial workflows. This established the required data fields, document types, GST checks, exception rules, access controls, and processing statuses.

Document Intelligence Design

The extraction workflow was designed to support multiple invoice formats, including scanned images, digital PDFs, multi-page documents, tables, and handwritten content. Standard output schemas ensured that data from different layouts entered one consistent financial structure.

Serverless Pipeline Development

We created an event-driven processing architecture using AWS Lambda with Python 3.11, Amazon API Gateway, Amazon Textract, and Amazon Bedrock. Each invoice moves automatically through document intake, OCR, data structuring, validation, storage, and status updates.

Security, Authentication and QA

Amazon Cognito was integrated for secure JWT-based access, while S3 encryption and versioning protected invoice documents and processing history. Quality assurance covered extraction accuracy, schema validation, GST checks, authentication, multi-page invoices, concurrency, and error handling.

Cloud Deployment and Monitoring

The platform was deployed using scalable AWS managed services with Multi-AZ availability and pay-per-use infrastructure. Amazon CloudWatch monitoring and alerts provide visibility into system activity, processing failures, performance, and operational health.

From 5,000 to 15,000 Invoices Per Month

The platform increased monthly invoice processing capacity from 5,000 to 15,000 invoices while reducing manual data entry by 85%. Invoices can now move from upload to structured and validated financial data in approximately two to three minutes.

AI-powered extraction, schema validation, GST checks, and confidence scoring give finance teams greater control over data quality. Real-time job tracking and CloudWatch monitoring improve operational visibility, while uncertain or incomplete records can be directed to the appropriate team for review.

With encrypted storage, authenticated access, automated workflow orchestration, and scalable serverless infrastructure, the platform delivers a 300% improvement in productivity while supporting future invoice growth. Its pay-per-use AWS architecture also enables the client to expand processing capacity without maintaining dedicated servers.

Planning an AI-powered invoice processing or accounts payable automation platform? Talk to Devine Globe Technologies about building a secure, scalable solution for invoice data extraction, GST validation, financial workflow automation, and cloud-based document processing.