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Aporia is an AI observability and monitoring platform designed to help machine learning teams detect, investigate, and resolve issues in production models. Originally built by Aporia Technologies, the tool has been acquired by Coralogix, a leader in observability, to combine AI monitoring with broader infrastructure observability. Aporia solves the problem of model degradation, data drift, and performance anomalies by providing real-time alerts and explainable insights. Its core capabilities include model monitoring, data drift detection, bias detection, and root cause analysis. The platform integrates with popular ML frameworks and deployment environments, making it suitable for data scientists, ML engineers, and DevOps teams. Aporia fits into workflows that require continuous monitoring of model health, compliance, and business impact. By joining Coralogix, Aporia now offers a unified observability solution that spans both AI and traditional applications.
4.3/5
High, consistent, and on-brand
Clean and minimal
Monitor and debug machine learning models in production.
Integrates with ML frameworks like TensorFlow, PyTorch, and deployment platforms such as Kubernetes and AWS SageMaker.
Freemium with paid tiers
Features with the highest value for users are highlighted here.
Real-time model monitoring
Data drift detection
Prediction quality analysis
Automated alerts
Model explainability
Multi-framework support
Integration with Coralogix
Data Scientists
ML Engineers
DevOps Teams
Compliance Officers
Product Managers
Startups
Enterprise AI Teams
Research Institutions
Healthcare AI Teams
Financial Services
Free
Pro
Weekly intelligence on AI strategy, operations, and market shifts. No noise. No narrative. Direct to your inbox.
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