Case description
Manual processing for mould detection of an agar plate is time-consuming, has low accuracy, and the results can vary from lab to lab due to manual bias, thus require double control.
Method
Replaced the manual analysis of the agar plate by a deep learning-based AI algorithm that could count colonies and identify mould species.
Result
Reduced lead-time by 25 %.
Increased precision by 30 %.
Eliminated manual bias in the analysis.
Introduced transparency and traceability.
