The first

machine learning health monitoring solution.

Monitor model

Monitor all your live machine learning models from a centralized dashboard.

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Any ML model in production

Classical ML or deep learning. Scikit-Learn or Pytorch.

Centralized dashboard view

Quickly know when things are happening. Get your team in sync

Quick setup and easy integration

Just connect 3 endpoints and you’re ready to go

How does Sanau work?

Import Sanau library

Pip install sanau library to speed up your development process

Add few lines of code

Easily capture all important metrics in your training and deployment stages

Start monitoring

Login to your Sanau account and monitor all your models from single dashboard

Trust model

Most organizations recognize the benefits of deploying AI but worry about hurting customer trust through biased models.

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Build trust

Bias detection, bias prevention, bias correction

Remain compliant

Comply with regulations, directives and guidelines

Auditability and explainability

Trace back every prediction, every inference. Keep a log for audit purposes

Set alerts

Know exactly when your models start degrading. Receive custom alerts when your distributions shift and when your model is due for re-training.

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Distribution shifts

Know when your input data distributions are shifting for different types of data including numeric, image and text

Customize alerts

Get notified when your model accuracy drops below your SLAs, internal metrics or customer expectations

Bias warnings

Get warnings when your models displays bias towards certain group of people based on sex, age or race

Keep your machine learning models healthy

Monitor the health of your ML models in production from a central dashboard