Deploy data science models in real time with ModelOps

Deploy, monitor, and govern any model from any framework in any environment
Deploy data science models in real time with ModelOps
Deploy, monitor, and govern any model from any framework in any environment

How ModelOp Gives You Control

IT teams face many challenges: how to deploy, monitor, and govern all the machine learning and AI workloads their company builds, including the variety of open source options like R, Python, and Tensorflow. This can be a daunting task for IT professionals, as they must support deployment as part of core business operations.
ModelOps Data Platform
Use any framework, language, or workbench
R, Python, Scikit, Tensorflow, C, Matlab, Scala. ModelOp supports them all. Apply your model to real-time data arriving in Kafka or REST or run it in batch against a database or file system.
ModelOps Expertise
Centralize model artifacts & metadata
ModelOp captures all of the metadata you need to run and manage your model. From docker containers, to data schemas, to dependent libraries, to model source code. Giving you a complete view of your models.
ModelOps Data Science
Track key metrics
Model utilization, data skew, accuracy, latency, overall model productionization time, SLA, and other metrics are captured in one place and in a consistent format.
ModelOps IT
Customizable model life cycles
Define workflows to manage the entire life cycle of a model from development to testing, production to continuous improvement, and eventually, to retirement. ModelOp provides an out-of-the-box integration with Github, Docker, Kubernetes, HDFS and SQL databases.

How Your Work Will Be Transformed

As an IT professional charged with enabling ML and AI in your organization, you are fundamentally concerned with reducing the impedance between model development and putting a model into business. ModelOp Center provides out-of-the-box capabilities to support this effort as well as the ability to build new capabilities and assets needed for your organization. Every new model doesn’t need to be a new IT effort!

How ModelOp Is Unique

ModelOp takes a fundamentally different approach to enabling ModelOps for large enterprises. ModelOp Center is built with the critical capabilities required for IT operations teams to support data scientists and the business in getting models into business quickly, consistently, and reliably. Our solution leverages a set of simple but powerful abstractions that enable long-term, uniform deployment success for the enterprise, fundamentally designed from the core to drive automation for an enterprise’s data science investments.
ModelOps Models into Business
Models should follow a uniform deployment process regardless of source
ModelOps Governance Icon
Data schemas should be defined by data science teams and supported by data engineering
ModelOps Navigation Icon
Data streams enable a model to effortlessly move from batch to on-demand applications.
ModelOps Line of Business
As is often the case, base architectures are critical to ensure both flexibility and scalability for the IT teams.

Explore the Impact of ModelOps

We have the experience and solution to help you harness the power of AI/ML at scale that will boost your core processes. Let’s create a unique solution together.