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Fixed costs for unlimited data

Monitor your ML model, data pipeline, data stream, or dataset - any volume, anywhere.

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All plans include:

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    Unlimited rows and predictions

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    Unlimited users

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    Monitoring 100% of the data, without sampling

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    Support for structured and unstructured data

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    Access to the full Observatory platform

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    12+ months of data retention

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    Privacy-preserving integration

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    Ability to sign up via the AWS Marketplace

STARTER

Self-service ML and data monitoring for individual practitioners


Included:

  • 2 Projects
  • Monitor ML models, data pipelines, or data streams with each Project
  • Up to 100 features/columns per Project
  • Community support

Free

Up to 2 Projects

No credit card needed

GET STARTED FOR FREEBOOK A DEMO

EXPERT

For small teams with more than two projects in production


Included:

  • Up to 25 Projects
  • Monitor ML models, data pipelines, or data streams with each Project
  • Up to 500 features/columns per Project
  • One organization
  • Email support

$50

per Project/month

CONTACT US

ENTERPRISE

For organizations with advanced scale and support needs


Included:

  • Unlimited projects
  • Unlimited features
  • Real-time monitoring
  • Custom monitors
  • Custom integrations
  • Enterprise level security and compliance, SAML
  • Dedicated support

CUSTOM

per Project/month

CONTACT US

STARTER

EXPERT

ENTERPRISE

Free plan

$50 per Project per month

Custom pricing

Scale

Number of Projects2 Projects25 ProjectsUnlimited Projects
Unlimited rows and predictionsChecked iconChecked iconChecked icon
Unlimited usersChecked iconChecked iconChecked icon
Free test projectsChecked iconChecked icon
Unlimited features per modelChecked icon
100% of the data monitored, no samplingChecked iconChecked iconChecked icon

Data

Data retention12 months12 monthsCustom data retention
Real-time metrics Checked iconChecked iconChecked icon
Streaming and batch dataChecked iconChecked iconChecked icon
Tabular, image, text, video, audio dataChecked iconChecked iconChecked icon
Data segments (prediction slices)up to 5up to 20Custom
Privacy-preserving data profilingChecked iconChecked iconChecked icon

ML/AI Models

Model comparisonChecked iconChecked iconChecked icon
Training data baseline monitoring Checked iconChecked iconChecked icon
All common model types Checked iconChecked iconChecked icon
Ensemble modelsChecked icon
Embeddings Checked icon

Monitors and alerts

Data quality monitorsChecked iconChecked iconChecked icon
Data drift monitorsChecked iconChecked iconChecked icon
Model performance monitorsChecked iconChecked iconChecked icon
Zero-configuration monitor set-up Checked iconChecked iconChecked icon
Seasonal and custom monitors Checked icon
Daily monitor granularity Checked iconChecked iconChecked icon
Hourly monitor granularity Checked iconChecked icon
Custom monitor granularity Checked icon
Real-time monitor granularity Checked icon
Email and Slack notifications Checked iconChecked iconChecked icon
PagerDuty and ServiceNow notificationsChecked icon
Custom Webhook actionsChecked icon
Retraining triggersChecked icon
API accessChecked icon

Platform Capabilities

Time machine view of data and model healthChecked iconChecked iconChecked icon
Interactive data investigation Checked iconChecked iconChecked icon
Root cause analysis and debugging workflow Checked iconChecked iconChecked icon
Model performance dashboard Checked iconChecked iconChecked icon
Executive summary dashboard Checked iconChecked iconChecked icon
Explainability-powered monitoring Checked iconChecked iconChecked icon
Correlation of alerts across pipeline steps Checked iconChecked iconChecked icon

Security and Compliance

SOC 2 CertifiedChecked iconChecked iconChecked icon
SAML SSO Checked icon
Role-based access controls Checked icon
Custom deployment modelChecked icon

Support

Community SlackChecked iconChecked iconChecked icon
Email support Checked iconChecked icon
24x7 support availability Checked icon
Dedicated Customer Success Data ScientistChecked icon
Enterprise SLAsChecked icon

Frequently Asked Questions

Can I use WhyLabs for free?

Yes! There are two ways to use WhyLabs for free.

The WhyLabs Starter plan is free to use now—and forever—for two Projects. You get all of the convenience of monitoring for data drift, data quality, and model performance combined with continuous data logging and profiling for unlimited data volumes along with many other great features, all included for free.

Secondly, the WhyLabs Enterprise plan offers a free trial period that’s optimized for your unique requirements. Please contact us and we will be happy to work out a custom trial period.

How do I get started?

Simply click here to create a free account and get started! The platform will guide you through all steps you need to onboard in just a few minutes.

For an overview of the process, you can take a look at the Onboarding guide in the documentation center.

Alternatively, contact us to schedule a call with our team. We’re happy to help you learn more.

How can I upgrade when I’m ready?

Upgrading is easy when you’re ready to move up from the Starter plan!

When you want to start monitoring more Projects, simply add them to your Project dashboard, and we’ll contact you about your account upgrade.

To upgrade to Enterprise, please contact us

What are Projects, Features, and Segments?

What is a Project?

A Project is any ML model, data pipeline, data stream, or dataset that you want to monitor in WhyLabs. The WhyLabs UI treats each of these items as a Project, so you can have flexibility in what you want to monitor.

What is a Feature?

A feature is a measurable property of the object you’re trying to analyze. In datasets, features appear as columns. In the WhyLabs UI, “Feature” is used interchangeably with “column”.

What is a Segment?

A Segment is a subset of your data or a prediction slice. You can segment your data based on any categorical column or feature in that data (be it for an ML model, data pipeline, data stream, or dataset). For example, you can choose to segment your data by geographies such as “zip code” or “country”, or human attributes like “gender” or “age range”.

Segments are powerful because they allow you to monitor changes in specific categories, classes, or other subsets of your data. They can detect bias or changes that may not be visible when only monitoring the dataset as a whole.

Projects in the Starter and Expert plans have a limited number of Features that can be associated with them. However, our platform can easily scale to monitoring Projects with thousands of features. If you have large ML models or datasets which need monitoring, please contact us to discuss our Enterprise offering.

Do I really not pay for predictions or rows?

That's correct! WhyLabs uses the whylogs open source library to collect summary statistics about your data. This approach enables us to provide highly accurate and scalable data and model monitoring, regardless of your data volume.

What data does WhyLabs collect?

None at all! WhyLabs relies on statistical profiles of your data generated by our open source library, whylogs. WhyLabs collects none of your data and your data never leaves your environment.

The whylogs library acts as an agent, capturing key statistical properties of data, such as the distribution, the number of missing values, and a wide range of configurable custom metrics. Using these summary statistics, WhyLabs AI Observatory is able to accurately represent the data and help you monitor your data and models.

To learn more about how WhyLabs guarantees your data privacy and security, take a look at our documentation or email us at [email protected].

Can I monitor both data and models?

Absolutely. By using whylogs, you can collect metadata about data regardless of whether it’s being used for an ML model, flowing through a data stream, or being transformed into a data pipeline.

WhyLabs supports a number of different types of monitors that you can configure based on your use case. If you’re monitoring an ML model, you may be interested in tracking data drift or model performance degradation. If you’re monitoring a data pipeline, you may prefer our data quality monitors, such as monitoring for missing values or data type changes.

Regardless of whether you wish to monitor data or models, WhyLabs can be configured to meet your needs.

What data types can I monitor?

All kinds!

You can monitor tabular, text, image, embedding, video, or audio data with WhyLabs. If you are interested in other data types, please contact us and we’d be happy to help.

You can also monitor batch or streaming data, regardless of the data volume.

What model types can I monitor?
WhyLabs monitors models in a model-agnostic way, so any model architecture is supported. For performance evaluation, we support the following output types:
  • Classification (single String)
  • Regression (single Numeric)
  • Embeddings (multiple Numeric)
  • Sequence (multiple Strings, multiple Numeric)
  • Recommendation system (multiple Strings)
  • Bounding box (multiple Numeric, plus maybe one String/Numeric)
  • Forecast (multiple Numeric)

Note that any custom output, including multiple output support is available.

How does WhyLabs monitor 100% of the data, without sampling?

Since WhyLabs relies on statistical profiles generated by whylogs, we easily scale to Projects with massive data volume, without having to resort to sampling. whylogs profiles are highly efficient (meaning that they store a lot of information in a small amount of computer memory), so it’s easy to send, store, and analyze them.

Other solutions will require you to sample data in your ML model, data pipeline, data stream, or or dataset. Sampling decreases the effectiveness of monitoring because it loses key statistical information about the dataset. To learn more, check out our Sampling versus Profiling blog post.

How do I get support for WhyLabs?

Our Starter and Expert customers have two options: opening a support ticket or asking a question in the community Slack. To open a ticket, log in your WhyLabs account. Expand the main menu on the top left-hand side and open “Support Center”. Follow the prompts to submit a support request. To ask a question over Slack, join the WhyLabs Slack Community.

What languages do you support?

Out of the box, whylogs is available in Python 3, Java, Scala and Apache Spark. In addition, for other languages, WhyLabs supports statistics collection via a REST container.

What payment options do you accept?

For the WhyLabs Expert and Enterprise plans we currently accept ACH or wire payments. You can also pay via the AWS Marketplace or reach out to us for a private offer. If you’d like to explore additional payment options, please contact us at [email protected].

Is WhyLabs SOC 2 certified?

Yes, WhyLabs has completed our SOC 2 Type 2 examination with zero exceptions. To request The WhyLabs SOC 2 Type 2 report, please contact your account manager or email [email protected]. To learn more about security at WhyLabs, take a look at https://whylabs.ai/data-privacy.

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