Censius is an AI Observability Platform built for AI/ML teams to monitor, analyze, explain, and debug models. By flagging issues such as poor data quality, model drift, bias, and degrading performance, it offers a single platform to bring together logs, input data, monitoring insights, and model details for root cause analysis (RCA).
Censius helps ML teams with
Configure countless performance monitors, data quality monitors, and drift monitors for unlimited models and model versions. Get instant alerts for violations.
Zoom into violations with a guided roadmap to locate the root causes of the problems and troubleshoot with precision.
Analyze monitoring and RCA insights by creating fully customizable dashboards to strategize and improve upcoming model versions.
Censius is for everyone
👨🏻🔬 Data scientists
Visualize, analyze assumptions, and explain how models are running in production
👷🏽♂️ Machine learning engineers
Proactively detect bugs and troubleshoot the ML pipeline without having to manually debug
👩🏾💼 Business executives
Understand model decisions and heath and communicate transparently with end-users using self-serve analytics
Go from months to hours
Contrary to existing industry practices of long and tedious manual methods of observability, Censius helps you to establish AI Observability as a foundational pillar of your ML pipeline within hours.
Integrate with your existing ML stack in minutes
Step 1 Create a project for a specific use case
Step 2 Upload dataset pertaining to a model
Step 3 Register the model
Achieve more with AI Observability
- Continuously monitor and log the necessary model vitals
- Reduce time-to-recover by detecting issues precisely and proactively
- Explain issues and recovery strategies to stakeholders
- Explain model decisions to customers
- Reduce downtime for end-users
- Build customer’s trust by deflecting issues like drifts, biases, and poor performance
Learn more about AI Observability
AI ObservabilityAPI ReferenceComing Soon
Need help? Email us at [email protected]