SensOS
Who Is the Company Behind SensOS?
- Seller: SensOS
- Year Founded: 2020
- HQ Location: Austin, US
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LinkedIn® Page: www.linkedin.com
2 employees on LinkedIn®
Total Products under this Category: 239
Last updated: November 01, 2026
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Highlighted products: SAP Asset Performance Management, Limble, Cryotos, GE Vernova APM, Fiix CMMS, Fracttal One, eMaint, and Nokia Warp 6.
Underlying data: [Grid® JSON](https://www.g2.com/categories/predictive-maintenance/grids.json?focus%5B%5D=sap-asset-performance-management&focus%5B%5D=limble&focus%5B%5D=cryotos&focus%5B%5D=ge-vernova-apm&focus%5B%5D=fiix-cmms&focus%5B%5D=fracttal-one&focus%5B%5D=emaint&focus%5B%5D=nokia-warp-6)
Sensys is a computerized maintenance management system (CMMS) that offers comprehensive and user-friendly features for both routine and complex maintenance activities. It helps you transform and digitalize your maintenance operations by simplifying work order creation, scheduling resources, prioritizing tasks, and executing them with standard work steps. At its heart lies the Digital Operations twin, with concepts designed specifically for operations and maintenance activities at asset-centric organizations. Sensys’s core concepts of Assets, Locations, Persons, Teams, and Inventory items (Spares, Tools, and Vehicles) are closely integrated with the maintenance workflow, giving you both power and flexibility to plan, schedule, and execute maintenance operations with ease.
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Our core offerings: - Signal AI - AI readiness and ROI assessment Identify where AI delivers value before you invest 👉 https://ai.gowitek.com/#assessment - Nexus AI - Enterprise decision intelligence platform Unify knowledge, enable governed AI-driven decisions 👉 https://gowitek.com/nexus-ai/ - ServitizeIQ - Predictive maintenance and service intelligence Turn asset intelligence into uptime and service revenue 👉 https://gowitek.com/servitization/ Built on Azure, AWS, Snowflake, Databricks, BigQuery, and microservices architectures, Gowitek delivers scalable AI systems designed for production environments not pilots. AI is easy. ROI isn’t. At Gowitek - we ensure it delivers.
All-in-one SaaS platform that helps you manage and automate all your service operations. Manage your Work Orders, assign Tickets, oversee all your Assets in all of your Locations and Track and Analyse all your Employees in one spot.
SETPOINT® CMS powered by OSIsoft PI® is a comprehensive online condition monitoring software solution that connects directly to the VC-8000 machinery protection system without the need for any additional intervening hardware. It provides powerful visualization tools such as timebase, orbit, full- and half-spectrum, bode, polar, air gap, shaft centerline, multi-variable trend, and other plot types specific to rotating and reciprocating machinery, allowing online condition monitoring analysis and machinery diagnostics.
SF2 Suite SE – State Intelligence on Your Own Data Many signals in. One comparable state out. SF2 Suite SE is the permanently free entry point into SF2 State Intelligence. It enables engineers, technicians, developers and industrial users to analyse multivariate machine and process data in a fundamentally different way: not only as individual sensor values, but as the combined state of the system they describe. Powered by SF2’s Semantic Folding technology, the software transforms heterogeneous sensor and process data into compact binary State Fingerprints. Temperature, pressure, vibration, current, speed, flow and other signals can be combined into a single state representation. Similar operating states generate similar fingerprints, making different points in time, operating phases or reference conditions directly comparable. From individual signals to system states Traditional monitoring often evaluates signals separately using thresholds, limits or predefined rules. This is useful, but it can miss changes that emerge from the interaction between multiple parameters while each individual value still appears normal. SF2 adds a system-level perspective. It captures the relationships within multivariate data and represents them as a State Fingerprint. Changes in machine or process behaviour therefore become visible as changes in the state representation. This allows users to explore questions such as: - Is the system behaving like it did under a known operating condition? - Is its state gradually drifting over time? - When did a relevant transition begin? - How similar are two production runs, batches or operating phases? - Is one machine behaving differently from comparable assets? No large labelled fault database required SF2 does not depend on conventional supervised fault classification or large collections of historically labelled failures. Depending on the application, the semantic model can be formed unsupervised from representative historical data. Known operating, maintenance or process conditions can then be stored as reference states. New State Fingerprints can be compared with these references through fingerprint overlap, providing a transparent measure of state similarity. Once a model is fixed and versioned, the runtime transformation and comparison are reproducible: the same input produces the same State Fingerprint and comparison result. Local by design SF2 Suite SE runs locally on Windows, macOS and Linux. Core analysis does not require a cloud service, allowing machine and process data to remain under the user’s control. The SE edition is designed for working with CSV data, making it easy to start with existing machine logs, sensor recordings or exported process histories without building a new data infrastructure first. What you can explore with SF2 Suite SE SF2 Suite SE can be used to investigate machine states, process drift, operating phases, maintenance conditions, production runs and multivariate behaviour across a wide range of applications. Typical data may come from manufacturing equipment, pumps, motors, machining processes, energy and water systems, test environments or complex industrial and life-science processes. The objective is not to replace SCADA, Condition Monitoring, automation or existing analytics. SF2 adds a complementary State Intelligence layer that makes complex multivariate system behaviour compact, comparable and understandable over time. Start with your own data Import your CSV data, create State Fingerprints and explore how the state of your machine or process changes over time. SF2 Suite SE is permanently free. No subscription. No mandatory cloud. SF2 – The Operating System for Machine States.
On Now Digital is changing the way you access and interpret electric power system information with SiteLine. This versatile asset management software empowers you to manage electric power information overload for good.
SmartHVAC monitors commercial air conditioning around the clock. Small wireless sensors go on the rooftop units, split systems and heat pumps you already have, any brand and any age, without opening the refrigerant circuit. The software learns each unit's normal, so a developing problem shows up as a plain-language alert on your phone instead of a breakdown. Built for restaurants, retail and multi-site operators, and the service companies that look after them. It works alongside your existing AC company.
It develops a user-friendly software preventing breakdowns, boosting quality and driving business value
Average Rating: 5.0/5.0
Total Reviews: 1
Rating: 5.0/5.0 stars
— Verified User in Alternative Dispute Resolution
SmartSignal is a predictive maintenance software developed by GE Vernova, designed to help industrial companies proactively predict, diagnose, forecast, and prevent equipment failures. By leveraging advanced analytics and machine learning, SmartSignal enables organizations to transition from reactive to proactive maintenance strategies, thereby reducing unplanned equipment downtime, extending equipment lifespan, and enhancing operational efficiency. Traditional maintenance approaches often lead to increased unplanned equipment downtime, reduced equipment lifespan, and operational inefficiencies. Reactive maintenance can result in significant financial losses due to unexpected equipment failures. SmartSignal addresses these challenges by providing early and accurate detection of emerging equipment issues, allowing organizations to shift from reactive to proactive maintenance. This proactive approach helps in reducing unplanned equipment downtime, extending equipment lifespan, and improving operational efficiency. One of the key features of SmartSignal is its use of AI/ML-driven Digital Twin blueprints. These blueprints utilize GE Vernova's extensive knowledge of failure modes, accelerating the time-to-value across investments. SmartSignal is equipment-agnostic, offering scalability and flexibility to monitor a wide range of assets. The software includes anomaly detection models that compare sensor readings to a machine's normal, predicted values for parameters such as load, temperatures, pressures, vibration readings, and ambient conditions. By detecting and identifying events and abnormal behavior through differences between real-time actual data and predicted normal behavior, SmartSignal provides early warnings of potential issues. In addition to anomaly detection, SmartSignal offers diagnostic analysis by comparing anomaly notifications with precursor signatures based on pattern and persistence. Utilizing data from over 19,500 rotating, fixed, mobile, and electrical assets, the software provides prioritized diagnostics with localized, apparent causes for each developing problem. Supported by charts of pattern differences, users can track and diagnose developing equipment failures effectively. The predictive analysis and time-to-action feature of SmartSignal allows engineers to forecast when equipment will reach an alarm limit and require immediate remediation. By using multiple analytics and desired time windows, teams can prioritize and schedule corrective actions to avoid unplanned downtime at minimal cost. This forecasting capability enables organizations to plan maintenance activities more effectively, reducing operational disruptions and associated costs. SmartSignal's unified dashboard provides a comprehensive view of critical data, allowing users to visualize, analyze, and act on alerts. This intuitive interface facilitates root cause analysis and tracking of maintenance success, offering a near 360-degree view of tagged assets in one place. The software's rapid time-to-value is supported by Digital Twins built on years of GE expertise in industrial manufacturing, operations, service, and software. With a growing Digital Twin catalog covering more than 330 common industrial assets, SmartSignal provides predictive, diagnostic, and forecasting analytics tailored for each monitored asset. For organizations seeking additional support, GE Vernova's Industrial Managed Services (IMS) offers a range of expert services to guide and facilitate SmartSignal success. GE Vernova monitoring centers worldwide provide 24x7 asset monitoring, issue triage and notification, remediation guidance, analytics management, and strategy consulting. IMS services are available with software purchase or subscription, or as a turnkey outsourced offering, eliminating the need to own or manage the software directly. GE IMS monitors thousands of assets globally and has saved customers over $1.6 billion in avoided costs. SmartSignal is also available as an integrated component of GE Vernova's Asset Performance Management (APM) suite, combining powerful analytics within a comprehensive asset and operations management solution. This integration allows SmartSignal data and results to be a core component of health dashboards and reports, reliability management activities, strategic planning, and other APM functions. In summary, SmartSignal by GE Vernova is a comprehensive predictive maintenance solution that empowers organizations to anticipate equipment issues before they occur, enabling proactive maintenance and reducing costly downtime. By leveraging advanced analytics, machine learning, and Digital Twin technology, SmartSignal enhances operational efficiency, extends equipment lifespan, and supports organizations in achieving their maintenance and reliability goals.
Sockeye is a work order scheduling and reporting bolt-on for your CMMS. How it works: Designed specifically to solve complicated, inefficient CMMS scheduling. Sockeye has seamless read/write integration with your CMMS. Sockeye’s automation assigns available labor with ready-to-schedule work orders from your CMMS to produce daily/weekly schedules with minimal effort and maximize efficiency. Schedules are live, easy to update with drag and drop functionality, visual, and easily accessible to the entire team. SMRP & custom KPI dashboards and reports keep you up to date with the latest, like schedule compliance, total backlog hours and why work was delayed. -Daily/weekly work order scheduling -Live status updates -SMRP/custom KPI reports -Month-to-month subscription -1 hour training. 98% Customer Retention Rate -Cloud-based/off-premise -API read/write integrations with any CMMS -Free trial using file-based integration (Excel)
Average Rating: 3.5/5.0
Total Reviews: 4
Rating: 4.0/5.0 stars
— Verified User in Financial Services