According to Software AG, it has already embedded Zementis’ ADAPA (Adaptive Decision and Predictive Analytics) into its Digital Business Platform to offer enterprises comprehensive insights for real time business analytics. The combination of Software AG’s real-time streaming analytics and ADAPA predictive analytics delivers precise business and technical insights into customer behavior, market dynamics, security risks and sensor information from the Internet of Things (IoT).
Karl-Heinz Streibich, CEO, Software AG said, “The impact of the Internet of Things on industry, business and society will dwarf anything we have experienced through technology so far.”
“This is now widely acknowledged by industry, as is the unique business insights that can be provided by combining predictive analytics, machine learning and streaming analytics. This combination has played a major role in the recent strategic IoT partnerships Software AG has established.”
Software AG claims to have made multiple IoT alliances in the last couple of months such as Bosch, Dell and Cumulocity, with an intent to integrate digital sensors and predicting maintenance requirements. These capabilities will now be enhanced through automated decisions based on machine learning for manufacturing, logistics, or any data heavy use case.
“Zementis was founded with the vision of delivering true interoperability for Artificial Intelligence, allowing machine learning and predictive models to rapidly move from development to deployment, allowing data-centric organizations and enterprises to easily incorporate AI into their routine operations,” said Michael Zeller, CEO, Zementis.
“Software AG’s open standards strategy empowers clients to manage heterogeneous IT architectures, and perfectly complements the vendor-neutral AI capabilities that our solutions deliver.”
The AI company states that machine learning and AI are key technologies for building smarter, next-gen IoT applications and are key competitive capabilities for innovative organizations. The company claims to have accelerated time-to-insight, and focused on the rapid operational deployment of predictive models for mission-critical applications such as risk scoring, fraud detection and predictive maintenance.
