
Cole and Jaenisch dig into AI poisoning in pharma manufacturing, how it hides in plain sight, and who should be accountable for catching it.
This case study shares why a leading biotech company reached out to Aizon to identify how artificial intelligence (AI) could be used to further optimize yield. The team was able to analyze five years of historical batch data to discover a direct correlation between hold up volume and time between process operations as well as generating millions of additional recovered revenue.






