Example Builds — AI Document Processing
Worked examples showing how we approach document processing problems — the architecture, the trade-offs, and the failure modes. These are reference builds we put together to demonstrate the approach, not delivered client projects, and the figures in them are modelled rather than measured.
For work we have actually delivered, see the IoT cost reduction case study on the blog.
Three worked examples of AI document processing — logistics, legal and insurance. Each walks through the problem, the architecture we would use, and where this class of system typically breaks. The scenarios and figures are modelled to show the approach, not measured from delivered projects.
Invoice Processing Automation
Scenario: logistics company
The Challenge
- • Processing 5,000+ invoices monthly
- • 15 staff members spending 120+ hours weekly
- • Manual data entry errors causing payment delays
- • Vendor complaints about slow processing
- • High operational costs ($180,000 annually)
Our Solution
- • Custom OCR + NLP model for invoice extraction
- • Automated vendor matching and validation
- • Integration with existing ERP system
- • Exception handling workflow
- • Real-time processing dashboard
Results Achieved
Contract Analysis & Review
Scenario: law firm
The Challenge
- • 200+ contracts reviewed monthly
- • Junior lawyers spending 80+ hours on initial review
- • Inconsistent clause identification
- • High billable hour costs for routine work
- • Client pressure for faster turnaround
Our Solution
- • NLP model trained on legal documents
- • Automated clause extraction and categorization
- • Risk assessment scoring system
- • Comparison with standard templates
- • Detailed review reports generation
Results Achieved
Insurance Claims Processing
Scenario: insurance company
The Challenge
- • 1,000+ claims processed weekly
- • 25 adjusters spending 200+ hours on document review
- • Slow claim processing leading to customer complaints
- • Inconsistent damage assessment
- • High processing costs ($300K annually)
Our Solution
- • Computer vision for damage assessment
- • Document classification and extraction
- • Automated fraud detection algorithms
- • Integration with claims management system
- • Real-time processing pipeline
Results Achieved
More Example Builds
Further reference builds showing the same approach
Medical Records Processing
Healthcare provider automated patient record digitization and analysis.
Financial Document Analysis
Bank automated loan application document processing and risk assessment.
HR Document Management
Corporation streamlined employee onboarding and document verification.
Proven Results Across Industries
Consistent outcomes that drive real business value
Want This Built for Real?
These are reference builds — the real version gets scoped to your documents, your volumes, and your accuracy requirements. First conversation is free.