Production data science

When you have a machine learning model and want to integrate it with your business applications, you need a production data science platform.

 

What is production data science?

Production data science is the full lifecycle of deploying machine learning models into your production environment and integrating them into your business applications. It’s the end-to-end process from connecting the models to the data sources, defining analytically-based decisions, managing the runtime environments, collecting the outcomes and responses, and monitoring the models for anomaly and drift detection.

The solution? The Quickpath Platform. Quickpath bridges the gap between the environment the data science team uses to build models and the deployment environment and standards corporate IT requires.  This approach provides a repeatable and consistent path to production for data and analytics driven decisioning. It results in more models deployed, more quickly and generating more business value from your data science practice.

 
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Connect

Connect to your production data stores, ML models,
& applications using prebuilt adaptors.

Define

Define your decision flow based on business rules, data, and models.

Manage

Deploy decision flows into execution, and monitor operation & business performance.

Learn

Collect responses
to refresh models, results of experiments, and new data training sets.

Govern

Manage models and approve workflows, 
version models, & decisions from
the same platform.

 
 

Pick a model. Any model.

Quickpath supports all the major modeling frameworks and algorithms so your data science team can use their existing tools with the Quickpath Platform.

Leverage predictive model scoring, machine learning, and AI using industry standard algorithms for propensity scoring, clustering, segmentation models as well as graph, NLP/NLU, image and facial recognition, and other deep learning applications. It supports Python, H2O, TensorFlow, R, Scikit-Learn, Keras, SAS®, Openface, Caffe2, Watson, Google, Azure, AWS ML cloud APIs, Domino Data Labs, IBM DSX and SPSS, Spark ML, graph databases, and more.

Shows how a data scientist can import an H2O model from a Jupyter notebook into the Quickpath Platform.
 

Bring Speed and Agility to Enterprise AI Initiatives

Quickpath accelerates integration of artificial intelligence and machine learning across the enterprise while understanding the realities of corporate IT standards and data security. Whatever you need to integrate for AI, we can help.

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No matter your machine learning maturity, Quickpath can help.

Maybe you’re at the beginning of your machine learning journey. Maybe you’re a seasoned traveller. Regardless of your place on the ML maturity curve, Quickpath’s platform and expertise can take you to the next level.

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Quickpath Expertise in Machine Learning

Years of experience back our collection, development, and integration processes. We’ll help you identify your best sources of data, develop models to work off of them, and integrate them with your existing platform or business. Contact us for consultation pricing.