78% of PyTorch Models Never Reach Production. I Built the Fix.

78% of PyTorch Models Never Reach Production. I Built the Fix. After 28 years shipping AI at scale, I got tired of watching good models die on the way to production. By Anil S. Prasad — Founder, Ambharii Labs | Head of Engineering & Product, Duke Energy | Top 100 Most Influential AI Leaders USA 2024 There is a number that has followed me across every organization I have worked in. UnitedHealth Group, Medtronic, Ambry Genetics, R1 RCM, Duke Energy. The number is 78. Seventy-eight percent of PyTorch models built in research never make it to production. This is not a data science problem. The data scientists are talented. The models are good. The math works. The problem is everything around the model. The audit trail that regulators demand. The compliance framework that legal requires. The drift detection that ops needs at 3am. The fairness analysis that the board is now asking about. The explanation that a clinician, an underwriter, or a grid operator needs before they trust the outp