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World's Leading Berry Producer

Cuts ERP Test Creation Time by 50%

50%+

Less Test Creation Time

80%

Match to Human-Authored Tests

70–75%

First-Version Accuracy

Food & Agriculture

Company Profile

  • World’s largest berry company
  • 750+ independent growers across 5 continents
  • 115,000+ workers, operations in 60 countries

The Challenge

💡

The Solution

Scale QA execution to match a fast-moving Oracle ERP migration
AI capability generating first-pass test cases with validation flows
Turn dense technical documentation into test cases far faster
Automated parsing of structured and unstructured docs at scale
Translate deep analyst expertise into execution at greater speed
Analyst-led design that augments expertise rather than replacing it
Preserve accuracy and control while accelerating test coverage
Full traceability from source requirement to generated test output

The Full Context

The organization embarked on a major ERP migration to Oracle, with hundreds of interconnected applications and business-critical processes in motion. QA analysts were spending up to two weeks per module writing and validating test cases from dense technical documentation. The bottleneck was not expertise but scale, traditional methods could not keep pace with the urgency of the transformation.

A purpose-built AI capability, developed with AuxoAI, was deployed to accelerate test case creation while preserving analyst context, control, and judgment. Rather than replacing the QA team, the solution augmented it, handling the heavy lift of test generation so analysts could focus on edge cases, coverage, and quality.

The Approach

The solution, Test Assist, was built to accelerate test case creation while keeping experienced analysts firmly in control.

1

Intelligent Documentation Parsing

Turned dense, static technical specs into dynamic insight. The system parsed structured and unstructured documentation at scale and built knowledge graphs mapping business logic, edge cases, and exceptions.

2

Automated First-Pass Test Generation

Produced draft test cases with built-in validation flows. Analysts reviewed and refined rather than authoring from scratch, cutting creation time from weeks to days to hours without sacrificing accuracy.

3

Traceability and Workflow Integration

Provided a clear line from each source requirement to its test output and slotted directly into existing QA tools and workflows, keeping analysts in full context and control.

The Impact

The AI-augmented QA capability delivered a 50%+ reduction in test case development time per module, 70–75% first-version accuracy, and 80% alignment with human-authored test cases.

The solution eliminated the manual bottleneck of hand-crafting test cases from dense technical documentation. Work that once took nearly a week per module now takes days, or hours, with greater confidence in the results. Inconsistencies gave way to standardized, traceable coverage across the transformation.

The organization now operates with an AI-augmented QA function that scales without added headcount. Analysts focus on edge cases, coverage, and judgment while first-pass generation is automated. Teams report stronger collaboration, clearer documentation, and tighter standardization across a high-stakes, enterprise-wide migration.

Project Highlights

Solution

AI-augmented QA capability

First-pass test case generation

Knowledge-graph documentation mapping

Results

50%+ less test creation time
80% match to human tests
70–75% first-version accuracy
Full requirement-to-test traceability

Ready to Scale Your QA with AI?