MontBlancAI
MontBlancAI is the central intelligence hub for process manufacturers, ingesting and normalizing data from sensors, PLCs, SCADA, MES and ERP into a unified operational layer that eliminates data silos; it applies AI-powered real-time anomaly detection to surface deviations beyond traditional thresholds, generates actionable insights via intuitive dashboards and root-cause diagnostics, and delivers predictive maintenance and continuous improvement recommendations. Its unified data layer cleans and structures vast streams of process data, enabling teams to increase production capacity, reduce operating costs, ensure consistent quality, and address labor shortages by uncovering untapped capacity and validating critical cycles. Accessible through a web interface and APIs, MontBlancAI acts as a digital twin of your production ecosystem, fostering cross-functional collaboration and data-driven decision-making across plant operations.
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SkySpark
SkyFoundry’s software solutions help clients derive value from their investments in smart systems. Our SkySpark analytics platform automatically analyzes data from automation and control systems, metering systems, sensors and other smart devices to identify issues, patterns, deviations, faults and opportunities for operational improvements and cost reduction. SkySpark helps building owners and operators “find what matters” in the vast amount of data produced by today’s smart systems.
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VictoriaMetrics Anomaly Detection
VictoriaMetrics Anomaly Detection is a service that continuously scans time series stored in VictoriaMetrics and detects unexpected changes within data patterns in real time. It does so by utilizing user-configurable machine learning models. In the dynamic and complex world of system monitoring, VictoriaMetrics Anomaly Detection, a part of our Enterprise offering, is a pivotal tool for achieving advanced observability. It empowers SREs and DevOps teams by automating the intricate task of identifying abnormal behavior in time-series data. It goes beyond traditional threshold-based alerting, utilizing machine learning techniques to detect anomalies and minimize false positives, thus reducing alert fatigue. Providing simplified alerting mechanisms atop unified anomaly scores enables teams to spot and address potential issues faster, ensuring system reliability and operational efficiency.
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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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