The maturity of any ML pipeline depends on automation – not just in data analysis and modelling, but also the quality assurance process. Wipro ensures the quality of AI/ML applications through our state-of-the-art testing methodologies.
Our ML pipeline testing not only ensures that the deployed AI/ML endpoint works as expected, but also that the underlying infrastructure triggers as per defined configurations. This can range from simple API triggers to changes in data or models. Additionally, monitoring and observability play key roles in AI/models, ensuring a smooth performance versus a speedy trade-off between models as per specifications. We believe that testing ML applications purely as black boxes won’t be sufficient enough to bring agility to the MLOps pipeline. Wipro ensures that the three core tenets of AI/ML testing are covered: functional tests (features and data), MLOps, and infrastructure. We ensure quick deployments through A/B and canary testing on production variants.
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