| Sector | Education technology |
| Engagement | Test automation, data quality validation |
85% automation coverage
2 days → 4 hours regression cycle
30% reduction in production defects
The Challenge
Our client operates an education technology platform where the product value sits in its data — institutional metrics, comparative analysis, and the reporting built on top of them.
That creates a testing problem most automation approaches handle badly. The interface can behave perfectly while the numbers underneath it are wrong. A chart renders, a report generates, a dashboard loads — and none of that tells you whether the underlying transformation produced the correct figure.
Conventional UI automation would have confirmed the platform looked right without confirming it was right. For a product whose customers make decisions on those numbers, that gap was the whole risk.
The Solution
We built automation that extended into the data layer rather than stopping at the interface.
The approach validated the transformations themselves — checking that source data flowing through the platform processing produced the expected outputs, and that aggregations, comparisons and derived metrics computed correctly against known inputs.
Interface testing sat on top of that as a second layer, but it was no longer carrying the burden of proving correctness on its own.
Reaching 85% automation coverage allowed the regression cycle to drop from two days to four hours — but the more important outcome was that the coverage now tested what actually mattered.
Business Outcomes
- 85% automation coverage achieved
- Regression cycle reduced from two days to four hours
- 30% reduction in production defects
- Data transformations validated directly rather than inferred from interface behaviour
- Reporting accuracy verifiable against known inputs
Facing something similar?