ARS Manager

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An agency management system designed for agencies writing direct bill auto and collecting payments in their office.

IBM Scale-up Power9 E Series

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The IBM Scale-up Power9 E Series comprises enterprise-class servers engineered to handle the most demanding, data-intensive workloads. Featuring the advanced POWER9 processors, these servers deliver exceptional performance, scalability, and reliability, making them ideal for mission-critical applications and large-scale data processing. With support for up to 192 cores and 64 TB of memory, the Power9 E Series ensures seamless integration into hybrid cloud environments, providing businesses with the flexibility and efficiency required to meet evolving IT demands. Key Features and Functionality: - High Performance: Equipped with POWER9 processors offering up to 192 cores, delivering superior computational power for complex workloads. - Scalability: Supports up to 64 TB of memory, accommodating extensive in-memory databases and large-scale applications. - Advanced I/O Capabilities: Incorporates PCIe Gen4 slots, doubling the bandwidth of previous generations, facilitating faster data transfer and improved system responsiveness. - Reliability and Availability: Designed with industry-leading reliability features, ensuring continuous operation for mission-critical tasks. - Cloud Integration: Seamlessly integrates with hybrid cloud infrastructures, enabling dynamic workload management and resource optimization. Primary Value and User Solutions: The IBM Scale-up Power9 E Series addresses the challenges of managing and processing vast amounts of data in enterprise environments. By offering unparalleled performance and scalability, these servers empower organizations to run complex applications efficiently, reduce response times, and enhance overall productivity. The advanced I/O capabilities and robust reliability features ensure that businesses can maintain high availability and data integrity, crucial for mission-critical operations. Furthermore, the seamless cloud integration provides the flexibility to adapt to changing workloads and business needs, supporting innovation and growth.

IBM Fully Homomorphic Encyrption (FHE)

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IBM's Fully Homomorphic Encryption (FHE technology enables computations on encrypted data without the need for decryption, ensuring data remains secure throughout processing. This advancement allows organizations to perform complex analyses and machine learning tasks on sensitive information while maintaining privacy and compliance. Key Features and Functionality: - Data Security Across All States: FHE ensures data remains encrypted at rest, in transit, and during processing, providing end-to-end protection. - Privacy-Preserving Computation: Organizations can perform computations on encrypted data without exposing it, facilitating secure data analysis and collaboration. - Integration with AI and Machine Learning: FHE supports the development and deployment of machine learning models that operate on encrypted data, enabling privacy-preserving AI applications. - Cross-Platform Support: IBM offers FHE toolkits compatible with various operating systems, including macOS, iOS, Linux, and Android, allowing developers to implement FHE across different platforms. Primary Value and Problem Solved: IBM's FHE technology addresses the critical challenge of maintaining data privacy during processing. By allowing computations on encrypted data, it eliminates the need for decryption, thereby reducing the risk of data breaches and unauthorized access. This capability is particularly valuable for industries handling sensitive information, such as finance and healthcare, enabling them to leverage cloud computing and third-party services without compromising data security. Additionally, FHE facilitates secure data sharing and collaboration, as organizations can analyze and process data without exposing it, ensuring compliance with privacy regulations and enhancing trust in data handling practices.

IBM IoT Consulting Services

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IBM IoT Services help you transform enterprise business models with insights from IoT data, and intelligent workflows built on emerging technologies.

IBM Wazi Developer

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IBM Wazi Developer for Red Hat® CodeReady Workspaces (IBM Wazi Developer) is a productive development environment which fully integrates into any enterprise-wide standard DevOps pipeline and empowers developers by providing a consistent, familiar development experience for IBM z/OS®

IBM Data Gate

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IBM Data Gate is a data synchronization solution designed to make IBM Z data available to cloud, analytics, and AI environments. It synchronizes data from IBM Db2 for z/OS and other IBM Z data sources, including IMS and VSAM data sets, to supported cloud and data platforms. The solution uses an integrated synchronization protocol to capture and propagate data changes while maintaining transactional consistency between IBM Z source systems and target environments. IBM Data Gate supports hybrid cloud architectures by enabling access to IBM Z transactional data for analytics, AI workloads, and modern applications without requiring direct access to production transaction systems. It is intended for organizations that need to integrate enterprise IBM Z data with distributed data platforms and cloud-based workloads.

X-Force Red IoT Testing

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Securing the connectivity of devices and the software that controls them.

IBM Safer Payments

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IBM Safer Payments puts modern machine learning into the hands of on-site fraud management teams. This enables them to adapt more quickly to changing threats and the introduction of new payment products by dramatically shrinking the time it takes to test and deploy new profiles, rules and models. Using a unique cognitive computing approach, IBM Safer Payments profiles the behavior of any entity and delivers best-fit analytics interactively to fraud professionals. This proven technology is already protecting some of the world's largest and most complex payment portfolios. Out think fraud by rethinking detection.

Kubeturbo

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Kubeturbo leverages Turbonomic's patented analysis engine to provide visibility and control across the entire stack in order to assure the performance of running micro-services in Kubernetes Pods, as well as the efficiency of underlying infrastructure.