Radically simplifies design, development, delivery, and management of cognitive processes that get smarter and better with time while ensuring that these self-learning systems are explainable and transparent in their operations. Our software includes a set of development and orchestration tools and a set of industry-optimized Accelerators.
Support for Any Model, Any Data
Cortex Fabric supports any model developed in languages such as R, Python, Java as well as frameworks such as TensorFlow, PyTorch, Scikit-Learn. Cortex supports models developed using Amazon SageMaker, IBM Watson, Google AI, Azure ML Algorithmia among others. With over 120+ connectors, Cortex Fabric supports connectivity to a variety of different sources including S3, Mongo, Postgres, Box, CRM, Adobe Analytics amongst others.
Orchestration and Composition
Cortex Fabric includes an open and extensible visual workbench, developers and data scientists can collaborate to create and deploy enterprise grade cognitive business processes that are composed of agents, skills, ML models, and datasets. Agents are reusable AI system patterns that solve an industry problem once it is trained with your data. Agents orchestrate the execution of skills that are reusable building blocks of ML models and logic that can be easily combined with datasets and skills.
At the core of Cortex Fabric is Profile-of-One, which gives you the tools you need to deliver contextualized and actionable insights. It includes a Profile Explorer UI interface, CLI commands, and a python library that Cortex Fabric users can employ to create a focused set of attributes and schemas for an entity that can then be applied to AI applications that serve entity-specific results (e.g. suggestion engines).
Any Cloud, On-Prem
Fabric hosts your data, models, runtime services, and compute where you need it—within your enterprise or on your preferred cloud (RedHat OpenShift, GCP, AWS, or Azure).
End to End AI Lifecycle
Cortex Fabric provides the necessary lifecycle capabilities for teams to develop, test, deploy, and manage AI systems as they move from development into production. It provides tools for data scientists to explore data and prototype models; for developers to orchestrate and integrate data and models to develop AI solutions; for system administrators to promote these solutions from a development environment into production; and for devops engineers to monitor and maintain deployed solutions.
The Cortex Fabric Accelerators are prediction engines that enable businesses to improve customer engagement and lifetime value; to boost employee expertise to streamline business processes and decisions; and to protect brand reputation and digital infrastructure from AI business risks. They are optimized to run in Cortex Fabric and include reusable skills, ML models, datasets, and agents.
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Case Study : Hyper-Personalized Mobile Shopping
Create an immersive experience in mobile shopping app by combining written story content with product content into a feed that would be tailored to the individual app user.
Case Study : Cognitive Service Experience
Healthcare payer handles over 6M calls per year in their contact center from customers inquiring about how certain claims were processed. When a customer calls, the customer service agent spends critical minutes on each call trying to explain.
Case Study : Trading Insights
The banking and financial services company sought a way to better differentiate and personalize their services to traders.
Case Study : Customer Segmentation and Targeting
The customer wanted to ensure the successful rollout and customer adoption of its mutual fund web based application. To ensure its success, the company sought to identify which of its customers had the highest propensity to adopt the new platform.