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WhyLabs Platform

Built for practitioners by
practitioners

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Infrastructure-agnostic AI monitoring and operations. Any data type at any scale.

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Easy to set up

Provision the platform using whylogs, our lightweight open-source library. Integrate with Python, Java, or Spark in a few lines of code.

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Privacy preserving

Interoperable with any ML infrastructure and framework. Generate real-time insights in your existing data flow.

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Cost efficient

Handle your large-scale data, keeping compute requirements low. Integrate with either batch or streaming data pipelines.

Amplify AI operations in four steps

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1

Instrument your
pipeline with whylogs

Simply install our lean, open-source library, which seamlessly integrates with on-premise infrastructure and all major cloud services.

For python pipelines
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2

Get real-time insights

Upon installation, the WhyLabs user interface immediately starts surfacing insights enabling users to:

  • Analyze input data and model outputs in real-time
  • Investigate how model features evolve over time
  • Root-cause and fix model performance decay
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3

Monitor for data quality
and drift

Enable one-click monitoring on all model features and predictions:

  • Catch data quality issues, data drifts and concept drifts
  • Choose the most suitable monitoring baseline for each model
  • Take action with timely alerts and notifications
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4

Collaborate with the right people

Insights can be easily shared and used for collaboration with the right stakeholders

  • Discover and share insights with fellow data scientists, ML engineers and managers
  • Set up a workspace in minutes. Plug notifications into existing workflows via Slack, email or PagerDuty.
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