Increase AI/ML model accuracy and reliability.
Prevent negative publicity due to quality issues related to bias.
Successfully integrate AI features into existing digital landscape.
Reduce AI testing cost of ownership.
We have a deep understanding of AI algorithms such as neural networks, decision trees, and support vector machines. Full test coverage includes supervised, unsupervised and reinforcement models.
We recognise the criticality of data pre-processing and feature engineering in AI models. Data cleansing, normalisation and feature extract techniques are used to optimise data quality.
Navigate the complexities of data partitioning, cross-validation, hyperparameter tuning and model selection. We train AI models and validate them using precise evaluation metrics.
At TestPro we help to address biases and ensure fairness in AI systems. Our proficiency in detecting, measuring and mitigating bias ensures ethical considerations are validated.
We know the challenges specific to AI testing, from black-box models to the need for explainability, interpretability avoiding concept drift and to defend against adversarial attacks.
TestPro’s experience covers the entire AI development life cycle. From requirements gathering to design, implementation, and deployment, testing activities are seamlessly integrated with your SDLC.
DELIVERED.
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