Monitoring & Continuous Operations

Monitoring & Continuous Operations goes beyond traditional lightweight tools to enable monitoring, root cause analysis, retraining and model validation in a continuous loop across large, complex, feature-rich models

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We are building the next generation application for Monitoring and Continuous Operations.

Monitoring

• The most comprehensive monitoring capabilities – at scale

• Create custom policies for each model

• Distance or window based monitoring of billions of data points

Root Cause

• Break through alert fatigue with custom alerts

• Drill down into model behavior across hundreds of features

• Identify cause of problem and take appropriate action

Retraining

• The right set of actions to take

• Best time to train for cost efficiency

• How to manually retrain or trigger automated retraining

Validation

• Champion / challenger deployments let you test models

• Canary and shadow options provide flexibility and insight

• Manually replace or automate the redeployment process

Our Customers Keep Models Trustworthy – At massive scale

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Hundreds of Features

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Tens of Thousands of Inferences/Sec

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Billions of Rows

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Designed for extreme scalability

Analyze billions of data points – in seconds and on commodity hardware.

Find pattern shifts and anomalies in massive amounts of production data. In real-time as well as in much longer time horizontally, such as years.

Deploy More Trusted Models into Production

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Manage Models with Confidence

Establish in real-time whether your ML models are behaving as intended. Is there drift or uncertainty? Has the data changed or have the patterns changed? With Vian monitoring, root cause analysis, retraining, and validation you can monitor in real-time for drift, uncertainty, explainability, data quality, and more, to ensure the integrity and reliability of models over time.

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Comprehensive, Scalable ML Model Monitoring

Are ML Models Increasing Risks, Bias, or Vulnerabilities for your Business – or are they Delivering Trusted Insights that Drive Transformational Decision-Making?

Learn why robust and scalable monitoring solutions are critical to minimizing the risk of bias in your hiring.

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ML Operational Excellence

Keeping models trustworthy after they go into production is hard – it requires knowing why models degrade, how to identify root cause, and what actions to take to remediate the issues. This needs to happen at scale, as more models with more features and more inferences get into production, and models are getting bigger and complex. Our next generation platform for model monitoring and continuous is the backbone for reliable, responsible, transparent, trustworthy, and cost-effective human-centered AI within an enterprise.

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