Censius & Cerebrium Partnership: Deploy & Monitor ML Models under one roof

The AI Observability Platform for Enterprise ML Teams

Get end-to-end visibility of your production models and adopt a proactive approach toward model management to continuously deliver reliable ML.

Loved by teams across the industries

A single platform for delivering enterprise level observability at scale.

Compare

Compare

  • Compare different model versions

  • Conduct data & feature quality checks

Validate

  • Verify model performance using metrics

  • Derive possible ROI out of ML initiatives

Automate

  • Automate post production workflow

  • Collect traffic and metadata logs

Monitor

  • Continuously monitor models for drifts

  • Get real time alerts on preferred channels

Explain

  • Proactively detect suspicious patterns

  • Explain decisions to customers with clarity

Analyze

  • Perform root cause analysis

  • Visualize model performance in dashboards

Censius AI
Observability Platform

Censius offers end-to-end AI observability that delivers automated monitoring and proactive troubleshooting to build reliable models throughout the ML lifecycle

Explore Censius Platform
  • Censius Monitoring

    • Automate model performance monitoring

    • Send real time alerts for violations

    • Increase ROI & reduce resource costs

    Learn About Monitoring
  • Censius Explainability

    • Analyze root causes of model decisions

    • Reduce model risks and time to resolve issues

    • Establish trust with model transparency

    Learn About Explainability
  • Censius Analytics

    • Get real time model performance data

    • Quantify ROI of ML models with dashboards

    • Share model performance data with other teams

Get started in 3 simple steps

Seamlessly integrate Censius through Java & Python SDKs or REST API and deploy it on cloud or on premise.

Get started, it's free
  1. 1

    Integrate SDK

    Register model, log features and capture predictions in just a few lines of code.

  2. 2

    Set up monitors

    Choose from dozens of monitor configs to track the entire ML pipeline.

  3. 3

    Observe

    Register model, log features and capture predictions in just a few lines of code.

Observability for Everyone

  • Detect and Analyze Model Drifts

    Automate the continous monitoring of models to detect drifts and outliers

  • Get Root Cause Analysis of Decisions

    Dig down on every model decision to identify and study the components that lead to it

  • Analyze Performance of Cohorts

    Slice the data into different cohorts to ensure decision consistency and elimination of bias

  • Gain end-to-end visibility of model performance

    Have complete visibility and understanding of model performance

  • Build trust with explainability

    Create trust among users by enabling model explainability for every decision

  • Study Business ROI

    Understand how a model is adding business value using specific business metrics and visualisation

  • Monitor Data Quality

    Eliminate missing, unexpected or extreme values to ensure data is consistent across the ML pipeline

  • Understand Feature Distribution

    Deep dive into what features are contributing to model performance and improve model output

  • Compare Model Versions

    Evaluate multiple model versions to analyze and identify the best performing ones

Observability for Everyone

  • Detect and Analyze Model Drifts

    Automate the continous monitoring of models to detect drifts and outliers

  • Get Root Cause Analysis of Decisions

    Dig down on every model decision to identify and study the components that lead to it

  • Analyze Performance of Cohorts

    Slice the data into different cohorts to ensure decision consistency and elimination of bias

  • Gain end-to-end visibility of model performance

    Have complete visibility and understanding of model performance

  • Build trust with explainability

    Create trust among users by enabling model explainability for every decision

  • Study Business ROI

    Understand how a model is adding business value using specific business metrics and visualization

  • Monitor Data Quality

    Eliminate missing, unexpected or extreme values to ensure data is consistent across the ML pipeline

  • Understand Feature Distribution

    Deep dive into what features are contributing to model performance and improve model output

  • Compare Model Versions

    Evaluate multiple model versions to analyze and identify the best performing ones

What people are saying

— Trishtana Banerjee // Security Associate, Meshcloud

Trishtana Banerjee

Security Associate, Meshcloud

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// Web Engineer, Factmata

Rajat Soni

Web Engineer, Factmata

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

Sr. Data Scientist, EY GDS

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 // Data Scientist, Nykaa

Rishav Ray

Data Scientist, Nykaa

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.

Get started, it's free

Censius automates model monitoring

so that you can 

boost healthcare

improve models

scale businesses

detect frauds

boost healthcare

improve models

scale businesses

detect frauds

boost healthcare

Start Monitoring