UnitX (FleX platform)
Who Is the Company Behind UnitX (FleX platform)?
- Seller: UnitX (FleX platform)
- Year Founded: 2018
- HQ Location: Milpitas, US
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LinkedIn® Page: www.linkedin.com
108 employees on LinkedIn®
Total Products under this Category: 191
Last updated: November 01, 2026
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Highlighted products: Ignition, Pelion IoT Connectivity, Insights Hub, Geotab, Augury, HiveMQ, TRACTIAN, and AWS IoT SiteWise.
Underlying data: [Grid® JSON](https://www.g2.com/categories/industrial-iot/grids.json?focus%5B%5D=inductive-automation-ignition&focus%5B%5D=pelion-iot-connectivity&focus%5B%5D=siemens-digital-industries-software-insights-hub&focus%5B%5D=geotab&focus%5B%5D=augury&focus%5B%5D=hivemq&focus%5B%5D=tractian-tractian&focus%5B%5D=aws-iot-sitewise)
Condition Based Maintenance is an IoT platform-as-a-service that uses streaming data from sensors to help you assess conditions, recognize warning signs, deliver alerts and automatically trigger maintenance. Connect and manage critical assets in near real time to increase customer loyalty and find new revenue opportunities.
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Viaduct is built to help teams get fast, AI-powered insights from high-dimensional time series data – so they can reduce downtime and improve asset performance.
MultiViz is an AI-powered vibration analysis and condition monitoring platform built to reduce false alarms. Threshold-based monitoring alarms every time a limit is crossed. MultiViz has no thresholds. It uses modes, which analyze groups of measurements together and tell you only when a new aggregate behaviour emerges. MultiViz then ranks what needs attention based on that new behaviour. It also gives vibration experts and reliability teams the tools to assess what the behaviour means and why. It works with the sensors you already have, and onboarding is quick.
"Plug-and-Play Web-Based Solution for Advanced Vibration Analysis"
Rating: 5.0/5.0 stars
— Christian S.
Novo AI WatchMen helps manufacturing companies understand what is really happening on their shop floor. The platform connects existing machines with external AI sensors and turns machine signals into clear production data. This allows teams to see when machines are producing, standing still, running idle, or losing time through short interruptions and microstops. WatchMen is especially useful for manufacturers with older or mixed machine parks, where direct PLC or SPS access is difficult, expensive, or not available. Instead of replacing machines or starting a large MES project, companies can start by making their current equipment measurable. The platform shows live machine status, OEE, availability, performance, cycle times, order progress, downtime reasons, machine comparisons, historical reports and shopfloor dashboards. Optional integrations with ERP, MES or BDE systems can connect machine data with production orders and planning data. Novo AI WatchMen helps production managers, operations teams and manufacturing leaders reduce guesswork, identify hidden losses and make better decisions based on real machine data.
AI, cloud, and data technologies have evolved rapidly. In contrast, traditional control systems remain rigid and incompatible. Legacy systems often involve complex hardware and wiring and rely on old control technology. Modern manufacturers need a way to bridge legacy and emerging technologies to overcome the limitations of traditional systems and enable next-level productivity, quality, and sustainability. embedded ocean was established to fill this critical gap between modern digital technologies and traditional industrial technologies to unlock the potential of software-defined control. Xentara is a modern edge platform for industrial control - designed to meet the demands of real-time automation at the edge, empowering software-defined control systems. It offers both event-driven and cyclic processes - ensuring real-time responsiveness while maintaining scheduled efficiency designed for ultra-high precision (up to 100kHz) - tailored for the most demanding applications. Xentara functions as a bridge between OT (Operational Technology) and IT (Information Technology) - enabling seamless integration across domains, boosting interoperability & semantic abstraction - unlocking smarter, more connected, modular, and efficient industrial systems.
Zometric Edge answers the question at the start of every digitalization project: how fast can you turn an unconnected shopfloor into a live data source? It is the Industrial IoT layer that connects any machine, PLC, sensor or database to real-time manufacturing intelligence, including the 90 percent of factory equipment that generates no usable data today. Universal connectivity: * RS232 and RS485 serial devices, PLCs and DCS, SCADA systems, smart sensors, databases and historians, automated inspection systems, MES and ERP. If it has an interface, Zometric Edge speaks to it * Protocol support includes OPC UA, MQTT and Modbus * Legacy machines without any data output join through custom retrofit devices that convert electrical signals into digital data, enabling automated downtime, OEE and quality capture without replacing equipment Built like infrastructure, not a gadget: * Bidirectional data flow: the platform does not just read the shopfloor, it can actuate machines and close the loop when a control limit demands it * Architected against the ISA 95 Purdue Model, from Level 0 equipment through Level 4 enterprise, so enterprise IT recognises the diagram and signs the PO without a six-month review * Edge compute and buffering: process and filter data at the source, buffer through network outages, and push when the link is back. No silent data loss * Browser-based setup: configure connections from a tablet, with no thick-client install and no IT-led rollout to bottleneck deployment One Edge layer feeds every consumer of machine data: real-time SPC, production and OEE tracking, predictive maintenance, live dashboards, inspection and statistical analysis across the Zometric platform. Aligned with ISA 95, ISA 88, OPC UA, MQTT and Modbus standards. Free pilot configurable in 2 to 3 weeks on your real machines.