Client
Services
Other topics
Yellow Canary partnered with Liveware to materially reduce the cost and effort associated with processing payroll, timesheet, and leave records held across fragmented and unstructured document formats.
Executive Summary
Liveware delivered an AI-enabled document intelligence and data-reconciliation capability that replaced manual, document-driven processing with a standardised, scalable workflow.
The outcome was a structurally lower cost-to-serve, improved processing efficiency, and audit-ready data outputs suitable for downstream reporting and assurance.
The Challenge
About Yellow Canary
Sydney-based RegTech company founded in 2017, providing AI-driven payroll compliance solutions for large employers. With 50+ employees, Yellow Canary has reviewed over $100 billion in payroll data, supporting complex workforces across multiple industries in identifying and resolving pay discrepancies.
The client’s operating model relied on human-intensive handling of:
- PDFs, scanned images, spreadsheets, and DOCX files
- Inconsistent templates and data structures
- Duplicate and partial employee records across sources
This resulted in…
- High labour costs
- Slow turnaround times
- Rework caused by data inconsistency
- Limited ability to scale
Traditional rule-based automation was insufficient due to document variability, necessitating an AI-led approach.
The Solution
Liveware applied a cost-reduction-first transformation model, focused on eliminating manual handling and rework:
Technology
Engineered a robust target-state data model meticulously aligned with complex reporting and assurance standards.
Integration
Standardised and reconciled high-volume datasets to establish a single source of truth for employee identities across disparate systems.
Experience (User Experience)
Leveraged AI-driven document intelligence to automate data extraction from unstructured and semi-structured sources, significantly reducing manual entry.
Collaboration
Implemented automated confidence scoring to isolate data exceptions, ensuring expert human intervention was utilised only where high-value judgment was required.
The Outcomes
Our solution resolved three key business problems for Yellow Canary: increased revenue, cost reduction & improved reputation through the following operational outcomes
80%
Reduction in manual processing effort across payroll and leave records
2-3x
Faster cycles for data consolidation and reporting
75%
Reduction in rework and error correction costs
Which resulted in the following qualitative impact:
- Reduction in rework and error correction costs
- Scalable capability without proportional headcount growth
- Improved confidence in workforce data quality
Stop managing the past.
Start building the future.
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