FAQ

What can Etiq help you with?

Test and monitor your data and AI pipelines. We cover tabular data and pretty much any modelling methodology. We actively maintain Etiq for the following libraries: XGBoost, LightGBM, PyTorch, TensorFlow, Keras and scikit-learn, however the tool can be used on pretty much any models from any libraries.

What issue types do you cover?

Data issues & leakage, performance and robustness related issues, different types of drift, bias and ethics; for more details pls. see our scan types section.

How do you deploy Etiq?

Sign-up for the dashboard, pip install the Etiq library, import it in your python or spark based IDE and you are good to go! For a quick start guide please see this link.

How long will it take me to get Etiq up-to-speed?

Some users report a time-to-value as low as 15 minutes. Because you can use Etiq as you would a library straight into any python or spark based IDE, you can use it straight away.

What if I have extremely large data? Can Etiq support?

Etiq has a spark version which can handle billion+ rows datasets comfortably.

What if I want to code up my own metric to use in tests and for monitoring?

Sure, we have ample functionality for you to include your own metric.

What if I want someone to tell me what tests and monitors to use?

Ping us an email: info@etiq.ai. We have extensive templates for step-by-step testing for: time series, financial sector classification, recommender models and many others.

How are you different from other testing/monitoring tools out there?

Privacy first & lightweight - no data/models leave your environment and you can use Etiq straight from your IDE/on your laptop

In depth testing - for any performance, drift or bias metrics (whether provided out-of-the-box or custom) we provide in depth root cause analysis for you to understand which segments of you data are underperforming and why.

How can I integrate with orchestration tools?

Here is an example of how to use Etiq + Airflow. You can use Etiq with any orchestration tools and also within environments such as Sagemaker, Databricks and pretty much any python or spark based environment.

Will my data leave my environment?

Your datasets or models will never be stored in Etiq or go out of your environment. However, if you are using our SaaS instance, results data only and data profiles (if you choose to store them), will be stored on the SaaS instance.

If you are assessing to see if Etiq is fit for your purposes: if you'd prefer not to send your results data to the dashboard, don't link your testing to the dashboard and results data will only be stored locally on your laptop or cloud instance. You can use Etiq locally during your session via the IDE.

When you decide to purchase Etiq, if you are on AWS you can do so with a one-click purchases from AWS Marketplace. Alternatively you can reach out for enterprise solutions.

How much will Etiq cost me?

Depends on the functionality you need, please see pricing here or directly from AWS marketplace.

How do I submit an issue/comment/ask for help?

Just email us: info@etiq.ai

Install best practice

We advise that (for security reasons):

In environments where multiple users should have segmented access to different dataset, the etiq library should be installed in a different virtual environment for each individual user.

In environments where the breach of segmented access is deemed high, imported modules should be inspected for manipulation of the Etiq.ai framework.

Please always respect your organisation’s security policies and, in doubt, please contact the person in charge of security within your organisation.

Licensing terms

Please see our licensing terms here.

Last updated