Capgemini’s AI Glass Box prescribes a checkpoint-based framework across the data science lifecycle. Through checkpoints such as Data Exploration (checks for missing values in data and numerical/categorical attributes of the dataset) and Model Monitoring (checks for consistency in column types), business users can spend significantly less time on technical aspects and focus instead on business solutions.
Banks rely on quick implementation for PoC before going for a wider deployment. With AI Glass Box, implementation time can be reduced by up to 10x due to pre-build veracity framework. From being able to fit into existing workflow and ML models to using a platform-agnostic Python approach, AI Glass Box offers a comprehensive framework for data science project validation.