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 […]
Drive business impact with transparent and explainable AI. Get started in minutes with Aporia’s ML monitoring and explainability solution.
With Aporia’s advanced Explainable AI toolbox, you can understand the ‘Why’ behind your ML model predictions. Discover which features impact your predictions the most, and easily communicate model results to key stakeholders. Using XAI, you can also simulate “What If” scenarios to see how they will affect your model.
Find the root cause of any issue and discover when it started using our Data Points and Time Series Investigation Tools.
Aporia makes it easy to slice and dice your data to quickly drill down into your model’s data points and the impact on prediction results.
With Aporia, you can analyze how your models arrive at their predictions, understand how a change in a feature impacts a prediction, and prevent issues like bias and drift in the future.
Use our Data Point Explainer to debug your data at a specific point, and then re-explain in one click.
Improve models in production
Know the why behind your model's predictions
Create automated & customized monitoring tailored to your specific use cases and models
Create automated & customized
See a live view of all models in one place
Instantly detect data drift, bias & data integrity issues
See why Data Scientists, ML Engineers and Business Stakeholders love Aporia.
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."
VP R&D
“ML models are sensitive when it comes to application production data. This unique quality of AI necessitates a dedicated monitoring system to ensure their reliability. I anticipate that similar to application production workloads, monitoring ML models will – and should – become an industry standard.”
General Manager AIOps
“With Aporia's customizable ML monitoring, data science teams can easily build ML monitoring that fits their unique models and use cases. This is key to ensuring models are benefiting their organizations as intended. This truly is the next generation of MLOps observability.”
Co-Founder | VP R&D
“ML predictions are becoming more and more critical in the business flow. While training and benchmarking are fairly standardized, real-time production monitoring is still a visibility black hole. Monitoring ML models is as essential as monitoring your server’s response time. Aporia tackles this challenge head on.”
Data Scientist
“We develop and deploy models that impact students' lives across the country, so it's crucial that we have good insight into model quality while ensuring data privacy. Aporia made it easy for us to monitor our models in production and conduct root cause analysis when we detect anomalous data."
“As an early stage startup, starting to launch ML models in the fintech sector, monitoring the predictions and changes in our data is critical, and Aporia has made it easy by providing the right integrations and is easy to use."
