Hi team, we're exploring machine learning to automatically classify and route tickets in Jira Service Management but could use some real-world advice—has anyone successfully implemented ML models (like NLP for ticket categorization or predictive routing) and integrated them with Jira? We're particularly curious about your tech stack (custom models vs. third-party tools), accuracy rates, and any unexpected challenges in production, as we're weighing whether to build in-house or use existing solutions like AWS Comprehend or Einstein AI—any lessons learned would be hugely valuable!
