AI Monitoring and Explainability Packed Into One Platform
The Censius AI Observability Platform is a one-stop solution for all post-deployment needs of ML models. Scale enterprise ML with automated monitoring, AI explainability, and analytics.
- AI Monitoring
Automate AI monitoring for model regression
Automate continuous model monitoring for performance, drift, outliers, and data quality issues using Censius Monitors. Get real-time alerts for performance violations on preferred channels.
Increase ROI and reduce resource costs
Automate and resolve time-to-resolve issues
Consistently serve high-performance models
Learn about Monitoring - AI Explainability
Gain trust by explaining predictions
Dive deep into a model’s decision-making by performing root cause analysis using Censius Explainability. Understand what features and data segments are responsible behind every model decision.
Analyze every model decision using AI explainability
Save time troubleshooting model issues
Gain complete visibility of model functioning
Learn about Explainability - AI Analytics
Analyze all AI performance in one place
Access real-time model performance with easy-to-understand and shareable dashboards. Continuously track various model performance metrics to drive decision-making.
Quantify ROI of ML initiatives
Share model performance with other teams
Get leadership buy-in on critical model decisions
Start Monitoring Models Now
98% of our users said it was easy to set up. But don’t take our word for it, experience it yourself.
Addressing the growing ML needs of enterprises
Censius enables ML teams to take control of their production models with its comprehensive features and easy-to-use interface
Comprensive Type of Monitors
Monitor Data Quality, Activity, Drift, and Performance
Comprensive Type of Monitors
Monitor Data Quality, Activity, Drift, and Performance
Set Alerts. Get Notified
Monitor Data Quality, Activity, Drift, and Performance
Comprensive Type of Monitors
Monitor Data Quality, Activity, Drift, and Performance
Get started in 3 simple steps
Seamlessly integrate Censius through Java & Python SDKs or REST API and deploy it on cloud or on premise.
- 1
Integrate SDK
Register model, log features and capture predictions in just a few lines of code.
- 2
Set up monitors
Choose from dozens of monitor configs to track the entire ML pipeline.
- 3
Observe
Track monitor violations and analyze issues without writing any code.
What people are saying
Trishtana Banerjee
I found Censius monitors to be thorough and easy to use with a good range of flexibility for both generic and specific monitoring needs. This adds velocity to AI solutions.
Rajat Soni
Censius provides transparency into the model decisions with its monitors and dashboard reports, cutting down the to-and-fro iterations. This saves a lot of time and effort.
Deepak Jhanji
Censius helps know if, when, and why the model has degraded and if it requires training. The continuous monitors are very convenient for clients as well as other stakeholders.
Rishav Ray
Censius has been really well built, and by using this we can definitely monitor all ML-based metrics. I see the value of leveraging it at the tail end of our ML life cycle.