Services provided
- Cloud Engineering.
- Serverless Architecture.
- Intelligent Document Processing
using Artificial Intelligence.
Platforms used
- AWS (Amazon Bedrock, Amazon Textract,
AWS Lambda, Amazon SQS, Amazon S3,
Amazon DynamoDB, Amazon SES, Amazon CloudWatch, AWS CDK)
Engagement length
- 8 weeks
Other stats
- ~9,000 purchase orders processed per month
- 83% cost saving compared to previous SaaS platform
- Accuracy improved from 55% to 95%
- Time to onboard a new customer reduced from 2-3 days to less than an hour
- ~35,000 serverless workflow events processed monthly
- 5 AWS Lambda functions powering the processing pipeline
- High-confidence purchase orders processed in under 1 minute
Background on the customer
Reece Group is one of Australia and New Zealand’s largest trade, plumbing, and building supplies organisations, supporting thousands of business customers across nationwide branch networks.
A significant proportion of B2B customers submit purchase orders directly from their own procurement systems via email. As order volumes continued to grow, Reece needed a more scalable and reliable approach to processing purchase orders while maintaining customer experience and operational efficiency.
Challenge
Purchase orders arrived in a wide range of customer-specific formats, layouts, and document structures. Processing these documents required significant manual intervention and relied heavily on template-based extraction approaches that became increasingly difficult to maintain as customer volumes grew.
The existing process created several challenges:
- High levels of manual handling and exception management
- Significant effort maintaining customer-specific document templates
- Delays in order processing and validation
- Limited auditability across document processing workflows
- Difficulty scaling operations as customer and order volumes increased
- Inconsistent handling of non-standard purchase order formats
- Operational dependency on specialist knowledge and manual review
Reece Group needed a solution capable of automatically extracting, validating, and routing purchase orders while preserving existing customer ordering behaviour.
Stack Highlights
The Approach
Codex designed and delivered a serverless AI-powered document intelligence platform on AWS to automate purchase-order ingestion, extraction, validation, and workflow routing.
Our approach included:
1. Designing an event-driven architecture using Amazon SES, S3, SQS, Lambda, and DynamoDB
2. Automating email ingestion and PDF document processing workflows
3. Leveraging Amazon Textract for OCR and document digitisation
4. Using Amazon Bedrock and large language models to perform schema-guided purchase-order extraction
5. Implementing confidence scoring and per-field validation to improve extraction quality
6. Building duplicate detection and validation capabilities before downstream order processing
7. Creating confidence-based routing to enable touchless processing for high-confidence orders while directing exceptions for human review
8. Implementing audit logging, lifecycle tracking, and operational monitoring throughout the workflow
9. Delivering the platform through Infrastructure as Code using AWS CDK
This approach enabled intelligent processing of highly variable purchase-order formats without relying on brittle template-based extraction techniques.
Technical Outputs
Codex delivered a production-grade intelligent document processing platform capable of automating purchase-order ingestion at scale.
Key outputs:
The resulting platform provided Reece Group with a scalable foundation for intelligent document processing while reducing operational effort and improving processing consistency.
Platform Highlights
AI-Powered Purchase Order Extraction
Combines Amazon Textract and Amazon Bedrock to extract and validate structured purchase-order information from highly variable customer documents.
Confidence-Based Automation
Purchase orders are automatically routed based on extraction confidence, enabling touchless processing for high-confidence documents while directing exceptions for review.
Event-Driven Serverless Architecture
A fully serverless design built on Lambda, SQS, and S3 scales automatically with document volumes while minimising infrastructure management overhead.
Complete Auditability and Traceability
Lifecycle tracking, structured logging, confidence scoring, and audit artefacts provide visibility across every stage of document processing.
Built for Document Variability
Designed to support diverse purchase-order layouts, terminology, pricing structures, delivery requirements, and customer-specific document formats without requiring ongoing template maintenance.
Business and Commercial Outcomes
The intelligent document processing platform delivered measurable improvements in
operational efficiency, scalability, and customer experience for Reece Group.
- ~9,000 purchase orders processed per month.
- 83% cost saving compared to previous SaaS platform.
- Accuracy improved from 55% to 95%.
- Time to onboard a new customer reduced from 2-3 days to less than an hour.
- Automated extraction, validation, and routing of purchase orders from customer
emails. - Reduced manual handling and template-maintenance effort across
order-processing teams. - Enabled high-confidence purchase orders to be processed in under one minute
from receipt to downstream validation. - Improved auditability through lifecycle tracking, confidence scoring, and
structured workflow state management. - Increased scalability by supporting growing purchase-order volumes without
proportional operational growth. - Improved operational visibility through monitoring, alerting, and workflow
analytics. - Preserved customers’ existing ordering behaviour, avoiding process change
requirements for trade customers. - Established a reusable AI-powered document processing foundation for future
business workflows.
The platform now enables Reece Group to process purchase orders more efficiently,
improve operational scalability, and deliver a faster, more consistent ordering experience
for customers.
An Enterprise Intelligent Document Processing Capability
Organisations typically deal with a high volume of unstructured documents across their operations, and handling these manually is slow, error-prone, and difficult to scale.
DocumentIQ is Codex’s reusable IDP accelerator built to address this, providing a consistent, configurable pipeline to extract structured data from any document and validate it against business rules.
At Reece Group, the document extraction service using DocumentIQ started with this single project, proving the capability in a real production context. That same service is now scaling to serve additional use cases, establishing DocumentIQ as an Enterprise Intelligent Document Processing capability that can be extended to new workflows without rebuilding from scratch.
With the foundation already in place, any new IDP use case becomes a matter of building on top of and integrating the reusable service into the new solution, never starting from scratch.
Talk to Us
We would love the opportunity to connect and understand more about the problems you are trying to solve.
Adrian Campbell
Chief AI Officer
Martin Campbell
Managing Partner
Get in touch to coordinate a meeting with one of our technical experts.
Australia: +61 7 3132 3002.
