What is the Quickpath Platform?

It is the Data and AI Fabric that connects your production data stores, AI and ML models, data science environment, and your business applications. It supports 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.

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.

Quickpath within the AI lifecycle

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Supports all major modeling frameworks and algorithms

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

See how easy it is to import an H2O model from a Jupyter notebook into 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.

Quickpath 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.

 

Key Capabilities

The Quickpath Platform has four key capabilities required for production data science.

  1. Decisioning Methodology

    We have packaged our best practices from hundreds of predictive analytics and real-time decisioning projects into the platform. It provides the ability to use models, data, and business rules to make decisions that drive the most business value. It includes real-time, batch, and event-driven use cases.

  2. Universal Model Management

    The platform includes a central repository of all models and decisions. Features include tracking of every model, outcome, and data used to make a decision, as well as reporting and analytics, and proactive drift and anomaly detection.

  3. Integration of people, process, and technology that support AI

    Open architecture to connect and integrate with all environments that AI impacts. Look at our Connectors here.

  4. Elastic Runtime Environment

    Configure and scale elastic runtime environments to run anywhere - on-premises or in a public cloud.

 
 

Decision Studio brings it all together: data, AI/ML, decisions, and integration.

Quickpath's low- or no-code design palette helps you be up to ten times as productive, compared to ground-up development. Orchestrate sophisticated decision flows, allowing for data acquisition and feature transformations, scoring, A/B tests, control groups, and even ensemble models. Then, test and validate everything right from the platform. Once you’ve designed your decision, deploy them easily to multiple production environments.

 

Universal Model Management

All your models are stored in a central repository. Enabling you to manage internal and external models no matter where they're running. Quickpath's powerful capabilities help everyone from data scientists to IT Ops keep tabs on model performance, operations, drift, and anomalies. Should anything deviate from historical trends, Quickpath will let you know.

 
 

Quickpath Platform Application Architecture