Document Intelligence for Legal Documents
"OCR on Steroids" - Achieving 63% efficiency gain processing civil case documents
Civil case registration | 63% efficiency gain | 85% error reduction | 70% faster processing
The Problem
Civil case documents start court proceedings. They arrive as PDFs from solicitors—every firm uses different templates. Clerks manually re-key names, addresses, and case details into the case management system.
It was slow, error-prone, and left sensitive data sitting in email inboxes.
- Civil case documents arrive as PDFs by email in different formats from various solicitor firms
- Clerks manually re-type names, addresses, case details into case management systems
- Time-consuming, error-prone process
- Sensitive data lingering in email inboxes
- Inconsistent document layouts, name variations, trading vs registered addresses
- Edge cases like companies in liquidation (liquidator details required)
Our Solution: "OCR on Steroids"
We built an AI-powered document intelligence solution that automatically extracts structured data from unstructured PDFs—handling complex layouts, edge cases, and variations.
- Built "OCR on steroids" - AI reader that extracts key fields from PDFs
- Handles inconsistent layouts, multiple address formats, complex edge cases
- Human-in-the-loop validation before sending to ICMS
- Direct integration with civil case management system
- Automated data validation and error checking
- Reduced sensitive data exposure in email
Challenges We Overcame
Inconsistent Formats
Challenge: Every solicitor firm uses different document templates and layouts.
Solution: Advanced layout analysis and field extraction models.
Complex Data
Challenge: Maiden names, trading names, registered addresses, companies in liquidation.
Solution: Months of testing and smart prompt design to handle edge cases.
Integration
Challenge: Send extracted data directly to ICMS without manual re-entry.
Solution: API integration with validation and human review checkpoints.
Accuracy Requirements
Challenge: Legal documents require high accuracy - mistakes have consequences.
Solution: Human-in-the-loop validation for critical fields, continuous learning.
How It Works
PDF Receipt
Civil case document arrives via email from solicitor firm.
AI Extraction
OCR and AI extract names, addresses, case details, handling complex layouts.
Human Validation
Clerk reviews extracted data for accuracy (quick check vs full re-type).
ICMS Integration
Validated data sent directly to case management system.
Case Registration
Civil case registered 70% faster with 85% fewer errors.
The Results
63% Efficiency Gain
Well above the initial 20% target. Clerks spend far less time on manual data entry.
85% Error Reduction
Automated extraction is more accurate than manual re-typing.
70% Faster Processing
Civil cases are registered much faster, reducing delays.
Less Sensitive Data in Email
Data extracted and moved to secure systems faster, reducing exposure.
Key Learnings
- Edge cases take time: Spent months wrestling with maiden names, trading addresses, and companies in liquidation—but it was worth it.
- Testing is essential: Extensive testing with real documents revealed edge cases that would have broken the system.
- Human-in-the-loop works: Quick validation check vs full re-entry saves time while maintaining accuracy.
- Exceeded expectations: 63% efficiency gain vs 20% target—smart prompt design and continuous iteration paid off.
Automate Your Document Processing
See how document intelligence can eliminate manual data entry and speed up your processes.