Perimattic
AI

How a Custom AI System Reduced Manual Document Processing by 67%

Teams spending 40+ hours weekly on repetitive document work — invoices, contracts, forms — cut that volume by 67% with a custom AI pipeline built for USA and UK operations.

Industry: Enterprise Operations & Automation|Tech stack: Java & Spring Boot, Apache Kafka, Python +5 more
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AI document processing pipeline extracting fields from invoices

67%

Reduction in processing time

90%

Decrease in manual errors

10x

Document volume growth

90 days

To positive ROI

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About the Client

About the Client

An organization managing large volumes of invoices, contracts, and forms across its daily operations needed to modernise its document-heavy workflows. Teams were spending over 40 hours per week on repetitive, low-value tasks — manual entry, validation, and routing — leading to frequent errors, rework, and slow approvals. The client needed a custom AI pipeline that could handle unstructured documents at scale, integrate with existing enterprise systems, and deliver measurable ROI quickly.

The Challenge

The Challenge

1

Time-Intensive Repetitive Tasks

Teams spent over 40 hours per week on repetitive, low-value document work — data entry, validation, and manual routing — leaving little time for strategic work.

2

High Error Rates and Frequent Rework

Manual processing led to frequent errors, resulting in repeated corrections, quality issues, and downstream operational delays.

3

Slow Approvals and Operational Delays

Document review and approval processes conducted entirely manually created bottlenecks that slowed business operations and decision-making.

Our Approach

What We Did

1Intelligent Document Understanding

  • Applied Generative AI for smart data extraction across complex and non-standard documents
  • Enabled context-aware recognition, eliminating rigid template dependencies
  • Achieved 95%+ accuracy even on unstructured and varied document formats
  • Leveraged LLMs to extract both structured and unstructured data reliably

2Automated Validation & Exception Handling

  • Automated document validation against existing enterprise records
  • Implemented confidence-based approval routing for high and low certainty documents
  • Enabled human-in-the-loop workflows for edge cases and exceptions
  • Integrated seamlessly with existing enterprise systems and data stores

3Workflow Orchestration & System Integration

  • Streamlined end-to-end document workflows to reduce turnaround time from days to hours
  • Built monitoring for processing accuracy, throughput, and exception rates
  • Enabled analytics-driven insights to continuously refine automation models
  • Delivered measurable ROI within a 90-day deployment window
Outcomes

The Results

67% Faster Processing Cycles

Document processing time reduced by 67%, enabling accelerated operational throughput across the organisation.

90% Reduction in Manual Errors

Automated validation achieved a 90% decrease in manual errors, improving data quality and compliance posture.

10x Scalable Operations

The system enabled 10x document volume growth without any increase in headcount.

Faster, Informed Decisions

AI-driven processing reduced review cycles from days to just a few hours.

ROI in 90 Days

The organisation realised positive return on investment within 90 days of deployment.

Built with

Tech stack

Java & Spring BootApache KafkaPythonAWSGraph DatabaseDockerApache AirflowTableau