There’s a fundamental problem with the typical ML model-development process: It evaluates models in terms of technical metrics like AUC, precision, or F-score, rather than business metrics like profit or savings – the stuff that actually matters to the company.

In this session, Gooder AI CEO Eric Siegel will demonstrate a new software category: ML valuation.

Why broaden ML evaluation to also include ML valuation? Because if you’re not measuring business value, you’re not pursuing business value. With ML valuation, you can explicitly navigate your modeling process toward monetary value.

Moreover, technical metrics fail to convince stakeholders to operationalize your model – they don’t care about AUC. With a business-user console that serves up business metrics, your stakeholder can make informed decisions to authorize model deployment.

Gooder AI can valuate any ML model, effortlessly serving up an interactive visualization to navigate your ML projects.