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What I found specifically cavalier was the statement that they "believe scale will be critical". That sounds like every ML/data driven start up that doesn't have enough data to actually make accurate models. There's a lot of fake it til you make it in startups like these.

What rigor would look like to me is something like:

(1) Do a historical analysis of who skips court and why.

(2) Come up with a plausible intervention strategy to solve problems identified in (1)

(3) Test your strategy in a well designed pilot and calculate it's effectiveness

(4) Validate your pilot results on a larger scale

(5) Offer your product commercially nationwide



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