Developing and evaluating multiple models in parallel, each experimenting with inputs, architectures, hyper-parameters and infrastructures.

Demystify the science with comparative evaluation.

Simplifying evaluation with objective, binary score for each experiment.

Supported by tools and rubrics to simplify "human-in-the-middle", increasing frequency and automation. 

Ranking experiments with aggregate scores from user feedback. Visible to PMO to measure progress in real-time.

Clear thresholds for model progression from POC to production.

Automated ROI estimates. Deep observations of infrastructure costs and usage to evaluate choices, architectural decisions, model performance, adoption and continuous improvement.​