Functions, Users, and Comparative Analysis
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We’re super excited to share that Aporia is now the first ML observability offering integration to the Databricks Lakehouse Platform. This partnership means that you can now effortlessly automate your data pipelines, monitor, visualize, and explain your ML models in production. Aporia and Databricks: A Match Made in Data Heaven One key benefit of this […]
Fundamentals of ML observability
Metrics, feature importance and more
We’re excited 😁 to share that Forbes has named Aporia a Next Billion-Dollar Company. This recognition comes on the heels of our recent $25 million Series A funding and is a huge testament that Aporia’s mission and the need for trust in AI are more relevant than ever. We are very proud to be listed […]
Create ML monitoring tailored to your specific needs, models, and use cases in minutes. Customize metrics and dashboards to bring model performance to life with Aporia’s ML observability platform.
Use Aporia’s magically-simple monitor builder to create over 50 different customizable monitors for data drift, bias, data integrity issues, performance degradation, and more in minutes.
Choose from automated monitors or code-based monitors to create ML monitoring that fits your specific use case and models.
Get a single pane of glass with everything you need to know about your models in production with Aporia. Instantly build your own custom dashboards for your specific model use case. From fraud detection to demand forecasting, and credit risk, gain the most relevant insights about your ML models at any time.
Want to implement your own custom monitoring logic? Or define your own monitoring metrics?
Select Absolute Values, Anomaly Detection, or Change in Percentage to begin creating your own custom metrics – or take customized monitoring to the limit with Aporia’s code-based Python monitors.
Thousands of data science & ML teams use us to achieve their AI goals
All ML stakeholders benefit from a custom ML observability experience
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Customize Aporia’s ML monitoring and dashboards to identify areas for model optimization, and translate insights into action. Track key metrics and easily detect drift, performance degradation, and model decay to ensure your models are always performing at their best. Understand feature impact with XAI and investigate the root cause of any issue in production.
In under 7 minutes, deploy Aporia on your AWS, Google Cloud, Azure, or Databricks account. Centralize Connect directly to the data source where you store your models’ predictions, whether on BigQuery, Snowflake, PostgreSQL, S3, or any other data store.
Integrate seamlessly with other MLOps tools, like Vertex AI, MLFlow, Sagemaker, and Kubeflow, and get a unified view of all your models in production.
Aporia helps to reduce costs and improve the ROI of machine learning projects. Customize dashboards to highlight business metrics that drive revenue. By leveraging Aporia's advanced analytics capabilities, gain deep insights into the value your models provide and how it impacts the business.
ML Engineering Team Lead
As a company with AI at its core, we take our models in production seriously. Aporia allows us to gain full visibility into our models' performance and take full control of it.
Create ML monitoring tailored to your specific needs, models, and use cases in minutes with Aporia’s ML observability platform.
Tailor dashboards to your needs for each one of your production models. Easily track the most important metrics, identify areas for improvement, and ensure your models are on the right track.
Proactive monitoring ensures your production models maintain high performance and reliability. Quickly detect drift, bias, performance degradation, and other production issues before they impact your business.