Create a new piece to your data pipeline, and gather feedback data from your AI models to keep them on track.

Implementing AI is one thing, but providing the data it needs to constantly improve will enable exponential value.

Create a data pipeline to provide feedback from your AI models in order to optimize performance.

Value

Continuous Improvement: enable ever-increasing ROI as your models gain actionable insights from feedback data.

Risk Mitigation: identify potential issues before they start by constantly monitoring your AI models in real time

Repeatability: build the foundational architecture to enable successful AI projects now and in the future

Details

Discovery phase: in depth look at all current models running.

Investigation phase: discover what data your models are producing and investigate what sets would be useful in refining that scope.

Implementation phase: implement feedback channel where useful.