Industrial Analytics SoftwareIndustrial analytics software that improves asset and process performance with a Process Digital TwinGet Your Free Trial Proficy CSense Overview Optimize with Industrial Analytics Software with 5-in-1 Capabilities Proficy CSense industrial analytics software uses AI and machine learning to enable process engineers to combine data across multiple sources and rapidly identify problems, discover root causes, predict future performance, and automate actions to continuously improve quality, utilization, and productivity.Uniquely providing five analytics capabilities in one package, Proficy CSense helps organizations around the world to achieve rapid business value. Engineers and data scientists can analyze, monitor, predict, simulate, and optimize and control setpoints in real time.Additionally, Proficy CSense provides capabilities to mine insight from historical data and rapidly develop, test, and deploy simple calculations, predictive analytics, and optimization and control solutions to reduce variability and improve operations. Download Proficy CSense Datasheet Outcomes Reduce Process VariabilityCombine data and use analytics and machine learning to improve process variability Speed TroubleshootingUse data to troubleshoot causes of asset and process performance issues rapidly Increase Engineering ProductivityProficy CSense’s visual analytics accelerate problem detection and improve efficiency Decrease DowntimeMonitor and ensure health and performance of base-layer PID control loops Optimize with a Process TwinMine new insight from industrial data to maximize return on assets Improve Data IntegrityValidate and clean raw sensor data at the source to ensure integrity of downstream systems Load More Customer StorySkjern Paper uses AI/ML to improve product quality and reduce wasteLearn More View All Customer Stories Enhance Engineering ProductivityCreating a Process Twin for smarter manufacturing is easy with Proficy CSense. Visual drag-and-drop analytics accelerate time to value and reduce dependence on data scientists and programmers. Online demos enable rapid mastery of the software with easy-to-follow demonstrations and guided simulations. Rapid wizard-driven data mining for engineers for fast time-to-insight Easy visual drag-and-drop functional blocks for subject matter experts and engineers Analytic solution templates without programming: simple calculations, data cleaning, maths, statistics, machine-learning models, real-time optimization, and advanced process control Access to popular script languages and CSense SDK for powerful analytic solutions with plug-and-play incorporation of Python, and 3rd party .Net content Read Machine Learning and Analytics View All Products CSense EditionsRuntime Edition⦁ For permanent production, deployment, and management of analytic solutions⦁ Includes Architect and Runtime ManagerDeveloper Edition⦁ For data analysis and analytic solution development and testing⦁ Includes both the Continuous and Discrete & Batch Troubleshooters, Architect, and Runtime Manager components for solution development and testing purposes onlyTroubleshooter Edition⦁ For offline, ad hoc, and on-demand data analysis, process modelling, and troubleshooting⦁ Includes the Continuous and Discrete & Batch Troubleshooters, along with all data connectors Where to Buy? Where to Buy? Leverage GE Vernova’s partner ecosystem of deep domain knowledge and industrial expertise.Our Partner Ecosystem Resources Blogs Videos Additional Resources FAQs FAQs What is Proficy Csense? Proficy CSense is industrial analytics software used to improve manufacturing performance by analyzing and optimizing process and control data. It helps reduce variability and improve KPIs like throughput, yield, recovery, emissions, and downtime. Using AI, ML, and optimization algorithms, CSense supports offline or real-time analysis and control, with flexible deployment on-premises, at the edge, or in secure cloud environments like AWS and Azure. What is industrial analytics software? Industrial analytics software is used to optimize asset, process, and operations performance using OT data across the production value chain. Because this data is often siloed and complex, AI, machine learning, and optimization algorithms are used to uncover insights and correlations that are difficult to detect manually. These tools support root cause analysis, performance prediction, quality improvement, and reductions in waste, energy use, downtime, and emissions. How is industrial analytics software used in manufacturing and industrial operations? Manufacturers use industrial analytics software to improve operational performance by analyzing time-series data from sensors, control systems, and historians. It helps identify inefficiencies, predict failures, monitor process stability, and optimize control loops. These insights support continuous improvement across production, maintenance, and quality—for example, by detecting equipment wear early, uncovering sources of variation, or recommending adjustments to reduce energy or material waste. How does industrial analytics software help improve operational efficiency and productivity? Industrial analytics software identifies inefficiencies, process drift, and bottlenecks by analyzing historical and ongoing operations data. It enables teams to take corrective action—such as tuning control loops, adjusting setpoints, or improving equipment maintenance strategies—before issues impact performance. These optimizations help reduce downtime, energy use, and material waste, while improving throughput, consistency, and product quality. What industries benefit the most from implementing industrial analytics software? Industries with complex processes and large volumes of operational data benefit most from industrial analytics—especially Food & Beverage, Consumer Packaged Goods (CPG), Automotive and Discrete Manufacturing, Water and Wastewater, and Utilities. These sectors use analytics to improve product quality, reduce waste, enhance efficiency, and increase yield and uptime. Other industries—such as Metals & Mining, Chemicals, Pharmaceuticals, and Paper—also gain value by applying analytics to optimize control strategies and reduce process variability. What are the key features to look for in industrial analytics software? Look for solutions that support the full industrial analytics journey—from exploring and analyzing raw data to monitoring performance, forecasting outcomes, simulating scenarios, optimizing setpoints, and executing control actions. Strong platforms also offer flexible deployment options (on-prem, cloud, edge), integration with time-series data sources like historians and SCADA, and prebuilt templates that accelerate time to value for common manufacturing challenges.Proficy CSense uniquely brings all five capabilities—analyze, monitor, predict, simulate, and optimize—into one proven platform. It includes out-of-the-box templates for high-impact use cases such as sensor health monitoring, PID control loop tuning, alarm pattern recognition, anomaly detection, process centerlining, statistical process control, and multi-objective optimization. These features help manufacturers reduce variability, improve quality, and boost yield without starting from scratch. How does industrial analytics software process and analyze large volumes of operational data? Industrial analytics platforms process large volumes of time-series and event-based data using a combination of in-memory, batch, and streaming analytics methods. Depending on the use case, they may analyze data continuously, at scheduled intervals, or in response to specific triggers. These platforms are designed to work with high-frequency data from historians, sensors, and control systems—extracting insights that support timely decisions without overwhelming storage systems or delaying action.Proficy CSense integrates tightly with Proficy Historian to support sub-second and even microsecond data resolution. It can execute analytics on a scheduled basis for tasks like model training, or in streaming mode to support closed-loop optimization and autonomous actions. What is the role of industrial analytics software in predictive maintenance and downtime reduction? Industrial analytics software supports predictive maintenance by identifying subtle patterns in operational data that signal early-stage issues—such as sensor drift, valve wear, or control loop instability. By detecting these signs before they escalate into failures, teams can prioritize maintenance, avoid unnecessary interventions, and reduce the risk of unplanned downtime. This proactive approach improves asset reliability, extends equipment life, and lowers maintenance costs.Proficy CSense can automate alerts or initiate corrective actions, such as adjusting setpoints or switching equipment into standby mode to prevent disruptions. For example, it can detect increasing cycle time in a pump, correlate it with declining efficiency, and automatically flag the issue or adjust control logic to reduce system strain—helping teams avoid costly breakdowns. How does industrial analytics software integrate with other systems like SCADA, MES, and ERP? Most solutions integrate using open standards such as OPC, MQTT, REST APIs, ODBC, and OLEDB to connect with existing systems. This ensures data can flow across SCADA, MES, ERP, and analytics platforms for unified insights.Proficy CSense supports all these protocols directly or via custom connectors, enabling seamless integration with diverse industrial environments. This flexibility allows users to pull data from multiple sources—such as a historian, MES, or lab system—combine it for advanced analysis, and send results or recommendations back into operational systems to drive timely action. What role does artificial intelligence (AI) and machine learning (ML) play in industrial analytics software? AI and ML technologies are used in industrial analytics to detect patterns, train predictive models, and continuously improve performance based on new data. They help manufacturers forecast demand or downtime, simulate process behavior under varying conditions, and uncover root causes of quality or yield issues—far beyond what manual analysis can achieve.Proficy CSense uses AI and ML to monitor, predict, simulate, and control operations. For example, CSense can detect an early drift in sensor behavior, simulate the downstream impact on product quality, and trigger an optimized control response—either as a recommendation or a real-time automated action in closed-loop systems. What are the challenges of implementing industrial analytics software in complex environments? Common challenges include siloed or low-quality data, lack of standardization across sites, and change management during implementation. Success depends on strong data infrastructure, stakeholder alignment, and tools that support flexible deployment and collaboration.Proficy CSense addresses these challenges by supporting reusable templates, centralized analytics management, and scalable deployment across plants and teams. For example, a team can develop a model to detect energy inefficiencies at one site, validate it, and then deploy it enterprise-wide—accelerating value while maintaining consistency. How does industrial analytics software contribute to Industry 4.0 and digital transformation? Industrial analytics software transforms raw OT data into insights that power real-time visibility, predictive intelligence, and data-driven optimization—cornerstones of Industry 4.0. It enables smarter automation, supports predictive maintenance, and reduces energy and material waste—allowing manufacturers to move from reactive to proactive and autonomous operations.These tools also help organizations break down data silos, standardize processes across sites, and accelerate digital maturity. By bridging the gap between operations and IT, industrial analytics lays the foundation for scalable digital transformation. The result is greater agility, improved decision-making, and more resilient manufacturing operations. What are the cybersecurity considerations when using industrial analytics software? Organizations should ensure data remains secure and under their control, especially in autonomous or closed-loop applications. Analytics models must be reliable and tested, and systems must follow strong access control and encryption practices.Proficy CSense can be deployed securely within a customer’s firewall or virtual private cloud (e.g., AWS or Azure) and supports safe, validated analytics-driven actions that preserve process safety and decision reliability. How can industrial analytics software support multi-site operations and scalability? Analytics platforms that support centralized management and template reuse allow companies to build solutions once and deploy them across multiple plants. This creates consistency while still allowing for local customization.Proficy CSense enables global collaboration by allowing subject matter experts to create analytics templates, validate them at pilot sites, and then scale them across facilities—creating a flywheel of shared knowledge and accelerated value. Customer Stories Customer Stories How Can We Help You? If you would like more information on any of our products and services, please take a moment to fill out the form below. We look forward to connecting with you! Thank you for getting in touch! We’ve received your message, One of our colleagues will get back to you soon. Have a great day!