As someone who’s spent way too many cycles watching ML projects stall in experimentation hell, I love how Plexe flips the workflow: diagnose → explain → deploy, all in plain English. The evaluation transparency (feature importance, bias checks, robustness) is the real differentiator, not just faster ML, but auditable ML. Curious how you’re thinking about governance over time? For example, automated retraining thresholds or drift detection tied to real business outcomes. Either way, this looks like one of those “inevitable” products that make it easier for smaller teams to ship serious intelligence. 👏