The main operational challenges include integrating the model into actual business workflows like support dashboards and sales cadences, dealing with data permissions across departments, handling legacy system latency, and managing feature drift where production data differs from training data. The gap between development and operations often causes timeline delays more than coding sprints.
The main operational challenges include integrating the model into actual business workflows like support dashboards and sales cadences, dealing with data permissions across departments, handling legacy system latency, and managing feature drift where production data differs from training data. The gap between development and operations often causes timeline delays more than coding sprints.
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The main operational challenges include integrating the model into actual business workflows like support dashboards and sales cadences, dealing with data permissions across departments, handling legacy system latency, and managing feature drift where production data differs from training data. The gap between development and operations often causes timeline delays more than coding sprints.
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