Use Cases

• ML Model Monitoring: Aporia can be used by data scientists and ML engineers to monitor the health and performance of their ML models in real-time, ensuring optimal performance and identifying any issues such as drifts, bias, or data integrity issues.
• Root Cause Analysis: The platform can help data scientists and analysts to identify patterns, new opportunities, and pinpoint the root cause of any issues with their ML models.
• Explainability: Aporia offers insights into the logic behind your models' predictions, making it useful for anyone who needs to understand how their ML models are making decisions.
• Big-Data Support: The platform can connect directly to your data lake without duplicating your data, making it useful for organizations that work with large amounts of data.
• Customization: Aporia allows tailoring dashboards to track inference trends, data behavior, and performance, making it useful for organizations that need to track specific metrics related to their ML models.
• Recommender Systems: Aporia can be used to monitor and optimize recommender systems, ensuring that they are providing accurate and relevant recommendations to users.
• Fraud Detection: The platform can be used to monitor fraud detection models, identifying any issues with model performance and helping to improve accuracy.
• Natural Language Processing (NLP): Aporia can be used to monitor and optimize NLP models, ensuring that they are accurately processing and understanding natural language.
• Responsible AI: The platform can be used to ensure that ML models are being developed and deployed in a responsible and ethical manner, with features such as bias and fairness monitoring.
• Compliance & Security: Aporia can be used to ensure that ML models are compliant with regulations and secure from potential threats.