Predictive AI with Red Hat AI

Predictive AI uses data to forecast a highly likely prediction of what could happen in the future. With the right AI platform, you can connect patterns, historical events, and real-time data to predict future outcomes with extremely high accuracy. 

With Red Hat® AI, organizations can build, train, serve and monitor predictive models, all while maintaining consistency across the hybrid cloud.

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How can predictive AI help your business?

Predictive AI helps businesses make informed, data-driven decisions, at a faster pace. Here are just a few ways predictive AI can be applied at the enterprise.

Financial planning

Financial planning

When your company’s setting its financial goals for the next 6 months—or the next 5 years—your team can analyze future data trends with new levels of accuracy. Predictive AI can identify specific data points that can help you make informed decisions about your business, like whether to move forward with your current strategy, or pivot. 

This real-time data can help mitigate significant financial risks and further optimize business resources. 

Learn how to manage Predictive AI adoption in financial services.

Fraud detection

Fraud detection

Identifying risks of fraud or cyber attacks is easier when you can predict the bad actors well before they strike. Predictive AI can help you identify anomalies within your data and reveal pending threats. 

With the right AI tools, these threats can be avoided and private data can remain secure. 

Learn how SWIFT uses predictive AI for financial fraud detection.

Healthcare

Healthcare and early disease prevention

Predictive AI in healthcare can aid in early disease detection and help identify patient diagnoses to improve overall care. Predictive AI provides tools to analyze large volumes of patient information, as well as real-time data, to provide a faster, personalized treatment plan. 

When patterns and insights are analyzed faster, with higher accuracy, healthcare professionals can identify and prevent life-threatening risks they couldn’t before. 

Learn how HCA Healthcare uses AI to predict cases of sepsis.

Customer experience

Customer experience and sentiment analysis

Customer behavior can depend on historical data, market trends, or the day of the week. Predicting how customers will react can influence decision making, from marketing to supply chain strategy. 

Predictive AI allows you to combine pools of data from multiple sources (like online reviews, sales trends, and competitor messaging) and help you anticipate how—or when, or why—customers are going to behave. 

This will allow you to better understand your audience and better serve your customers. 

Learn how NTT COMWARE uses predictive AI to enhance city tourism.

Mechanical maintenance

Mechanical maintenance and error prevention

Mechanical maintenance and error prevention can be improved with predictive analytics and pattern recognition. Predictive AI can track patterns through historical and real-time data and send alerts when it recognizes potential mechanical failures, irregularities, or routine maintenance check-ups.

Predictive AI can help you fix what’s broken, before it impacts employees, customers, or company resources. 

Learn how Airbus uses predictive AI to deploy applications faster.

How Red Hat AI can help

Red Hat AI provides a flexible foundation and the latest open source technologies to bring AI models from experiment to production faster. To simplify enterprise AI adoption at scale, our platform prioritizes flexibility, accessibility, and efficiency. 

We can help you overcome AI challenges that make it hard to scale such as cost, complexity, and deployment constraints. 

Scalable AI infrastructure

Red Hat AI provides a consistent, unified platform that helps teams scale predictive models on-premise, at the edge, or cloud environments. By eliminating infrastructure silos, teams can decrease the time it takes to get to production, while maintaining compliance. 

When a model is deployed to production environments, it is then able to make predictions. Red Hat AI provides a variety of frameworks to simplify model deployment, regardless of compute resource requirements. To simplify model deployment further, customers can also bring and deploy their own runtimes.

Streamlined model development

Red Hat AI provides a self-service platform that allows data scientists to build and scale predictive AI models more efficiently. With a consistent user experience, data engineers, application developers, and DevOps teams can collaborate more effectively in one place. 

Plus, with distributed workload capabilities, teams can achieve more efficient data processing across multiple environments at the same time. The solution allows teams to achieve faster data processing, tuning, and training across multiple cluster nodes simultaneously.

Hybrid cloud consistency

Red Hat AI allows teams to build, train, tune, and monitor AI applications consistently across the hybrid cloud. Developers can build their own model or bring the model of their choice, as a self-managed or cloud service. Businesses can evolve their AI strategy and move data securely, from on-premise to public cloud environments or at the edge.

With Red Hat AI, you have the ability to stay flexible, secure, and compliant, while reducing the costs of complex AI solutions.

Red Hat Support

Our dedicated support team of engineers can help you navigate our AI platform, the latest open source technologies, and our extensive partner ecosystem. From the operating system to the individual tools, we can provide the help you need to move your AI strategy forward.

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Red Hat AI

Tune small models with enterprise-relevant data, and develop and deploy AI solutions across hybrid cloud environments.

Customer stories

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Clalit

Clalit uses Red Hat AI to identify trends within 20 years of patient data to better understand disease behavior patterns and improve patient care.

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Agesic

Agesic uses Red Hat AI to standardize and scale the use of AI across Uruguayan government agencies with a consistent, hybrid AI platform.

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DenizBank

DenizBank uses Red Hat AI to provide a hybrid cloud environment that empowers data scientists to build and deploy more secure models and improve time-to-market.

Icon-Red_Hat-Media_and_documents-Quotemark_Open-B-Red-RGB “As an invaluable AI-driven solution, Red Hat OpenShift AI provides a streamlined environment that enables our data scientists to build and deploy more robust and secure models.”

Okan Çetinkaya

CDO – CAO, DenizBank

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