IBM Maximo Application Suite
IBM Maximo® Application Suite is a set of applications for asset monitoring, management, predictive maintenance and reliability planning.
Get the most value from your enterprise assets with Maximo Application Suite. It’s a single, integrated cloud-based platform that uses AI, IoT and analytics to optimize performance, extend asset lifecycles and reduce operational downtime and costs.
With market-leading technology from IBM Maximo, you’ll have access to configurable CMMS, EAM, APM and RCM applications, along with streamlined installation and administration, plus a better user experience with shared data and workflows.
Manage and maintain high-value assets with AI and analytics to optimize performance, extend asset lifecycles and reduce downtime and costs.
Streamline inspection processes with seamless, automated asset inspections driven by real-time data and artificial intelligence.
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Zolnoi
Accessible Industry 4.0 solution for your manufacturing company. We enable manufacturers to improve efficiency and reliability of production assets using IoT for data acquisition, proprietary AI for predictive analytics, and end-to-end platform for actionable insights. Integrate data from multiple sources. Optimize maintenance with predictive AI. Improve machine life and efficiency. Our data-driven approach leads to continuous improvement through. Condition monitoring IoT sensors and gateways, cloud-based data integration platform, AI-powered predictive analytics algorithms, and prescriptive analytics and actionable insights. Achieve tangible benefits through our software, estimated based on customer interactions and technology R&D.
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RemoteAware GenAI Analytics Platform
RemoteAware™ GenAI Analytics Platform for IoT transforms complex streams of sensor and device data into clear, actionable insights using advanced generative AI models. It ingests and normalizes high‑volume, heterogeneous IoT data, whether from edge gateways, cloud APIs, or remote assets, and applies scalable AI pipelines to detect anomalies, forecast equipment failures, and generate prescriptive recommendations in plain‑language narratives. Through a unified, web‑based dashboard, users gain real‑time visibility into key performance indicators, customizable alerts and threshold‑based notifications, and dynamic drill‑down capabilities for time‑series analysis. The platform’s generative summary reports condense vast datasets into concise operational briefs, while its root‑cause analysis and what‑if simulations guide preventive maintenance and resource allocation.
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AWS IoT Analytics
IoT data is highly unstructured which makes it difficult to analyze with traditional analytics and business intelligence tools that are designed to process structured data. IoT data comes from devices that often record fairly noisy processes (such as temperature, motion, or sound). The data from these devices can frequently have significant gaps, corrupted messages, and false readings that must be cleaned up before analysis can occur. Also, IoT data is often only meaningful in the context of additional, third party data inputs. For example, to help farmers determine when to water their crops, vineyard irrigation systems often enrich moisture sensor data with rainfall data from the vineyard, allowing for more efficient water usage while maximizing harvest yield. AWS IoT Analytics automates each of the difficult steps that are required to analyze data from IoT devices. AWS IoT Analytics is a fully managed and pay-as-you-go service that scales automatically.
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