Remove the Friction In Your Data Science Process

Keep your mission-critical intelligent applications continuously learning and improve the quality of their decisions. Improve model performance by running the models in the database and take intelligent actions in real-time.

See Splice Machine’s ML Manager in action.

Benefits for Data Scientists

With Splice Machine, data science teams are able to produce a higher number of more predictive models by experimenting frequently using diverse parameters and algorithms. Leverage updated operational data to concurrently train the model and minimize the time spent wrangling data.

Easily compare a number of models and seamlessly deploy the winner into production. Splice ML Manager provides end-to-end life-cycle management for your machine learning models to streamline and accelerate the design and deployment of intelligent applications using the most updated data.

Key Splice Machine Features

Experiment Freely

With MLflow as part of ML Manager, data scientists have complete freedom to experiment and compare models based on key parameters, versions, and...

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Train Models Continuously

Splice Manager data platform empowers data scientists to remove the latency in training their models by providing access to the most current data....

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Deploy Seamlessly

ML Manager provides data scientists with end-to-end model lifecycle management. Once the data scientists have selected their model, MLflow packages models into Docker...

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Run Models Faster

The Splice Machine Native Spark DataSource provides dramatic performance improvements for large scale data operations. The Native Spark DataSource works directly on native...

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Watch Our ML Manager Demo

Check out our webinar hosted by Splice Machine’s Ben Epstein