Constant feedback is an essential component of CI/CD. With applications being available 24/7, you need an AI platform that can monitor performance in real time. A360 business insights and customer alerts help you monitor proactively and understand how changes to AI models impact users.
Continuous feedback through Model monitoring is at the heart of MLOps, providing continuous visibility into your production ML. A360 Model Monitoring capabilities like data drift and concept drift allows data science teams to instantly detect, troubleshoot and resolve model issues early. Data drift identifies the deviation of the current data stream from the mean data values used to train the model. Concept drift identifies the deviation of the current model prediction output from the mean prediction values outputted during model training. These insights help to refine and react to changes to improve your models.
Promote Trust in AI
“AI is becoming more pervasive, yet most organizations cannot interpret or explain what their models are doing, resulting in a lack of trust and transparency. Organizations are not prepared to manage the risks of fast-moving AI innovation and are inclined to cut corners around model governance including security, escalating the negative consequences of misperforming AI models.”
Why Businesses Use A360 Monitor for Model Performance
Access metrics such as data drift, concept drift, outliers, specificity and selectivity that will provide insights on performance of the model as it relates to inputs and predictions.
Utilize metrics such as Resource Usage, Infrastructure Uptime, Availability, Hit Frequency, and Error Rate to ensure the health of your model-serving infrastructure.
Conduct root cause analysis with real-time insights into data, model, and infrastructure performance. A360 empowers your enterprise to make your AI workload reliable and efficient by getting to the root of problems quickly.
Customizable monitoring dashboards let you optimize your AI workloads to the right monitoring metric. Reduce noise and focus on the signals that matter most to your business.
Share and Collaborate on Reports
Need to have your model peer reviewed? Want to collaborate with other teams to troubleshoot model performance issues? You can share dashboards across projects with a single click.
Understand the “why” behind model performance with explainability that traces inputs to outputs. Unlock the black box of AI and bring transparency to your AI pipeline. Keep data integrity in check, and easily detect and address the impact of potential model bias to drive AI accountability and governance.