--- description: Busca información actualizada sobre Senseye PdM en GetApp Colombia. Lee opiniones verificadas y descubre sus funciones, características, precios y usabilidad. Compara Senseye PdM con productos similares hasta encontrar la opción adecuada. image: https://gdm-localsites-assets-gfprod.imgix.net/images/getapp/og_logo-94fd2a03a6c7a0e54fc0c9e21a1c0ce9.png title: Senseye PdM: precios, funciones y opiniones | GetApp Colombia 2026 --- Breadcrumb: [Inicio](/) > [Software de mantenimiento preventivo](/directory/1127/preventive-maintenance/software) > [Senseye PdM](/software/130871/senseye-pdm) # Senseye PdM Canonical: https://www.getapp.com.co/software/130871/senseye-pdm > Senseye PdM es una solución de mantenimiento preventivo basada en la nube diseñada para ayudar a empresas de sectores como el de la industria automotriz, fabricación, FMCG y petróleo y gas a realizar un seguimiento del tiempo de inactividad de la máquina y mejorar la OEE. > > Veredicto: 5 usuarios lo han valorado con **4.4/5**. De los mejores valorados en **Probabilidad de recomendación**. ----- ## Estadísticas y valoraciones rápidas | Métrica | Calificación | Detalles | | **En general** | **4.4/5** | 5 Opiniones | | Facilidad de uso | 4.2/5 | Basado en las opiniones generales | | Asistencia al cliente | 5.0/5 | Basado en las opiniones generales | | Relación calidad-precio | 4.0/5 | Basado en las opiniones generales | | Funciones | 4.4/5 | Basado en las opiniones generales | | Porcentaje de recomendaciones | 80% | (8/10 Probabilidad de recomendación) | ## Sobre el proveedor - **Empresa**: Senseye - **Ubicación**: Southampton, RU - **Constitución**: 2014 ## Contexto comercial - **Precio inicial**: US$ 7,50 - **Público objetivo**: 51-200, 201-500, 501-1.000, 1.001-5.000, 5.001-10.000, 10.000+ - **Despliegue y plataformas**: Cloud, SaaS, Web, Android (móvil), iPhone (móvil), iPad (móvil) - **Idiomas admitidos**: inglés - **Países disponibles**: Alemania, Australia, Brasil, Canadá, China, Estados Unidos, India, Japón, México, Reino Unido ## Funciones - API - Acceso móvil - Análisis de Big Data - Análisis de tendencias históricas - Asignación de recursos - Asset Lifecycle Management - Captura y transferencia de datos - Creación de informes y estadísticas - Gestión de datos - Gestión de dispositivos - Gestión de inspecciones - Gestión de pedidos de trabajo - Importación y exportación de datos - Mantenimiento de equipos - Mantenimiento predictivo - Mantenimiento preventivo - Programación del mantenimiento - Real-Time Data - Recordatorios - Seguimiento de equipos ## Opciones de asistencia - E-mail/Help Desk - Base de conocimientos - Asistencia telefónica - Asistencia 24/7 - Chat ## Categoría - [Software de mantenimiento preventivo](https://www.getapp.com.co/directory/1127/preventive-maintenance/software) ## Categorías relacionadas - [Software de mantenimiento preventivo](https://www.getapp.com.co/directory/1127/preventive-maintenance/software) - [Plataformas IoT](https://www.getapp.com.co/directory/1395/iot/software) - [Sistemas OEE](https://www.getapp.com.co/directory/1465/oee/software) - [Software de gestión de mantenimiento](https://www.getapp.com.co/directory/327/maintenance-management/software) ## Alternativas 1. [Fracttal One](https://www.getapp.com.co/software/111631/fracttal) — 4.6/5 (1773 reviews) 2. [The Asset Guardian (TAG)](https://www.getapp.com.co/software/111881/the-asset-guardian-tag) — 4.4/5 (12 reviews) 3. [Fiix](https://www.getapp.com.co/software/106721/fiix) — 4.5/5 (628 reviews) 4. [MaintainX](https://www.getapp.com.co/software/117239/getmaintainx) — 4.8/5 (1034 reviews) 5. [Limble](https://www.getapp.com.co/software/2049215/limble-cmms) — 4.8/5 (753 reviews) ## Opiniones ### "Senseye PdM" — 5.0/5 > **Dylan** | *30 de junio de 2021* | Envases y contenedores | Valoración de la recomendación: 9.0/10 > > **Puntos a favor**: The following features have been used most effectively within Smurfit Kappa: - Compare Dashboards - Thresholds and Prognostics - Trend and anomaly detections > > **Puntos en contra**: The system performs a 120 hour learning period for each asset that in on-boarded to the system. In this time, the system 'learns' what the 'normal' operating levels (vibration and current) are for each unique asset. If an asset is in poor condition when the system is installed, however, the system learns that the poor condition is the normal condition. > > As a result of the successful implementation of the Senseye PdM system at Jupiter Road, a number of potential breakdowns were avoided. With the support of the system, lost time has been avoided by completing preventative maintenance during periods of scheduled downtime, prior to the degradation and catastrophic failure of an asset. Further to the system’s ability to detail the issues with the site’s assets, it has also been used to confirm if the machines are in good health – and how exactly they operate under various conditions. This assurance has helped the team to confidently run the corrugator, to maximise production output. ----- ### "use of Senseye within the steel industry" — 4.0/5 > **David** | *30 de junio de 2021* | Minería y metalurgia | Valoración de la recomendación: 7.0/10 > > **Puntos a favor**: Senseye as an application is important to the future of industries like steel, where margins are tight and resources are limited. This sort of predictive application will be critical to the success of the industry as it will give us confidence in the condition of our assets and allow us, along with the use of other condition systems, to carry out targeted maintenance based on the actual condition of our assets. This will have a significant benefit to the availability of our assets and minimise unplanned outages. > > **Puntos en contra**: I find the user interface to be a bit 'clunky' , if it could be easier to get to the issue and get the feedback in a slicker way that would make it much easier. As mentioned the notification system needs to be developed to notify by exception, and also look at different ways to send the notifications. > > One of the strongest elements of Senseye is the team behind it, they have worked well with our team in integrating and moulding Senseye to work in the hugely varying environment of the steel industry. ----- ### "Using Senseye in a CNC machining context" — 4.0/5 > **Jan** | *29 de junio de 2021* | Maquinaria | Valoración de la recomendación: 6.0/10 > > **Puntos a favor**: the ease of integration and setup. the easy to use application The support and friendly nature of the team @ Senseye > > **Puntos en contra**: not getting the results we needed and it seems to have been over promised at sales pitches > > despite not having reached the results we needed I would still recommend their tool as long as you have made sure the Q of the data is adequate and able to pinpoint the failure you try to predict. It is not a magic system that sees failures out of any data, as it is often sold. ----- ### "Great system that gievs me a good overview of the condition of motors and gearboxes" — 4.0/5 > **Tim** | *28 de junio de 2021* | Productos químicos | Valoración de la recomendación: 9.0/10 > > **Puntos a favor**: The alert system that points me to the problem areas is invaluable, also the fact that i can scan over all the motors and gearboxes on my line without having to test each one individually is brilliant > > **Puntos en contra**: Id Like to be able to see the condition of all motors and gearboxes on one page as a quick glance rather than scrolling down a list > > Great so far and as we implement more features it is becoming more impressive ----- ### "Intuitive Senseye Software Scales Your Predictive Maintenance" — 5.0/5 > **Andy** | *1 de septiembre de 2019* | Ingeniería industrial o mecánica | Valoración de la recomendación: 10.0/10 > > **Puntos a favor**: The intuitive dashboard is excellent for front line users to gain insights quickly and direct their attention to the important few assets thereby freeing up their limited resources. The feedback loop via the maintainers dashboard is great to alert the support team at Senseye of the type of anomalies found, this information then leverages the power of their machine learning algorithms to get from Predictive to Prognostic. > > **Puntos en contra**: Most of my experience is around the front end where the engineers and maintainers interact with the dashboard. The latest iteration has improved over time to fit the end users needs and become more intuitive. All of my concerns of a couple of years ago have now been improved due to the excellent support team at Senseye. It's great that they have engineers with predictive technology backgrounds that understand the challenges that users face daily in an industrial environment. > > I was aware of Senseye as a software application to scale prediction in industry and came across users when I was training front line engineers at Nissan UK, Senseye was new to them and like most they were not open to change. That soon turned around when we started seeing real results coming in as the Senseye software gained more data insights that they could see resulting in avoiding unplanned events. I've found it very easy to navigate and as a former predictive practitioner could see the enormous benefits that scaling PdM brings; this was something we could only dream of just ten years ago\! ## Enlaces - [Ver en GetApp](https://www.getapp.com.co/software/130871/senseye-pdm) ## Esta página se encuentra disponible en los siguientes idiomas | Local | URL | | de | | | de-AT | | | en | | | en-AE | | | en-AU | | | en-CA | | | en-GB | | | en-IE | | | en-NZ | | | en-SG | | | en-ZA | | | es | | | es-CL | | | es-CO | | | es-MX | | | fr | | | fr-BE | | | fr-CA | | | nl | | | nl-BE | | | pt | | | pt-PT | | ----- ## Datos estructurados