Why predictive AI projects need an AI sidekick – a fraud detection example | Gooder AI

This is a demo of the Gooder AI chatbot, which serves as a thought partner and copilot for predictive AI projects – and helps business stakeholders understand everything.

Imagine that you – and your non-technical stakeholders – could ask endless questions of a virtual data scientist to guide your predictive AI projects. Gooder AI’s chatbot makes it possible. Watch this demo, which uses fraud detection as an example use case to show how it works.

Note: We added the AI voice to this demo video – the product doesn’t have narration yet.

For a more detailed overview of Gooder AI and demos for a few other use cases, watch this video: https://www.youtube.com/watch?v=6seERbo0-vE&t=4s

See also this demo of the Gooder AI chatbot for targeting marketing: https://www.youtube.com/watch?v=FP27JpdQsjI&t=10s

https://www.gooder.ai/

By incorporating an LLM chatbot into Gooder AI, we combine (hybridize) the best of both worlds: generative AI and predictive AI (aka enterprise machine learning).

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Here’s an overview of the Gooder AI project in general, beyond the chatbot feature in particular. Gooder AI is the business-user console for predictive AI projects.

PROFIT NOT AUC! HOW TO MAKE THE MUCH-NEEDED SHIFT FROM TECHNICAL METRICS TO BUSINESS METRICS

Data scientists always evaluate their AI models – but almost never valuate them. To pursue business value, stakeholders must visualize a model’s business performance. Gooder AI does just that.

There’s a fundamental problem with the typical model development process: It evaluates models in terms of technical metrics like AUC/precision/recall without also including business metrics like profit and savings – the stuff that actually matters to the business.

This is a serious problem – if you’re not measuring business value, you’re not pursuing business value. Further, those technical metrics fail to provide your client/stakeholder meaningful visibility – she doesn’t care about AUC. How is she supposed to authorize deployment?

That’s why Machine Learning Week founder and former Columbia professor Eric Siegel co-founded Gooder AI. It addresses this fundamental issue by way of its SaaS product, the first full-scale platform for machine learning valuation – to maximize the value of models by testing and visualizing their business performance.

Spoiler alert: Unlike technical measures, a model’s business performance (profit, savings, etc.) depends on how you use it. So assessing the business value requires a specialized visualization solution, one that allows you to interactively try out what-if deployment scenarios. This includes setting various business parameters, which are subject to change, and moving the decision threshold to estimate the potential deployed value.

Watch Eric demo Gooder AI and show how it drives ML deployment to maximize business impact.

https://www.gooder.ai/

Patent pending, Gooder AI, Inc.

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