MLRAM Monitors Your Predictive Model Accuracy and ROI

MLRAM monitors the ongoing accuracy of your predictive models realtime. It notifies you of reduced accuracy, significant changes in data or target values and automatically retrains your model. All of this integrating with any machine learning platform, and your application, in one line of code! MLRAM is the only product that automatically translates your model accuracy into business value and ROI.

The First Product for Predictive Model Accuracy and ROI Computation

Visualize Model Drift

Examine concept drift as changes in target actual values vs. predicted values at different levels of granularity.

Monitor Performance

Visualize the performance of your model while it is being consumed in real-time.

Calculate ROI

User configured form for revenue and investment of each event computes ROI for your predictive model automatically, saving hundreds of lines of code.

Pricing Plans

Free Trial

Up to 100 predictions versus actuals per month.

$0/month

Standard

Up to 1000 predictions versus actuals per month.

$200/month

Team

Up to 10000 predictions versus actuals per month.

$1000/month

Enterprise

For custom pricing please connect with one of our representatives.
All plans include up to 6 months of predictions versus actuals storage. Have questions or special requirements?
Contact Us

Other Products

Fastest, Most Accurate AutoML Training​

  • Auger’s patented Bayesian optimization search builds the most accurate possible predictive models
  • Proven against thousands of open datasets vs. Google, Microsoft, H20, AutoSKLearn, others
  • Guaranteed to outperform manual models or your money back

A2ML - Open Source Pipeline for All AutoML​​

  • Other ML providers offer APIs which need 100s of lines of code for full ML lifecycle
  • A2ML’s abstraction of a PREDIT pipeline allows train+predict in <10 lines of code (PREDIT wheel image)
  • Supports Google, Microsoft, other ML
  • Train with everything, pick the highest accuracy

Recent Posts

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Monitoring Machine Learning Accuracy in the Enterprise

Machine learning tools and practices continue to develop at a dizzying pace. The industry has moved on from running...

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Monitoring Machine Learning Accuracy

The biggest problem in machine learning model accuracy is that all models degrade. They perform well initially but as...

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Putting “Automating AutoML” to Work

In my last post I discussed why we at Auger believe that AI will eat software. Enterprises will move beyond just solving their biggest...

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