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Siemens (Munich, Germany)

Senseye Predictive Maintenance

Siemens cloud platform that automatically predicts machine failure and prioritises maintenance risks across multiple factories.

Go to website Senseye Predictive Maintenance alternatives
Shared spot1of 19 professional tools with a GDPR profileOur summary of what the provider itself publishes about your data: whether the data is stored in the EU (2 points), whether there is a certification or GDPR safeguard (1) and whether the provider is established in the Netherlands or the EU (1). 3 or 4 points is Strong, 2 Good, 1 Limited, 0 Unknown. How we measure in industry & manufacturing
GDPR: Strong
  • Provider based in the EU
  • Data in the EU according to the provider
  • Publishes certification/GDPR safeguards

Each tile is a professional tool in industry & manufacturing, the strongest GDPR profile on the left. 3 professional tools, like Senseye Predictive Maintenance, share the Strong profile: they share this spot. Click for that tool.

Priceon request
Free trialNone foundNot found on the provider's site when checked on 3 November 2026
BasedMunich, GermanyEU
ModelNot publicnot public which language model is used; generative AI copilot (Maintenance Copilot) and time series foundation models for forecasting (according to provider); cloud SaaS on Azure and AWS, all data storage and processing in EU data centres, EU SCCs in supplier contracts (according to provider); ISO 27001 (LRQA), ISO 9001, CSA STAR Level 1, NIS2-compliant (according to provider); user messages are reused by generative AI on an opt-out basis (according to provider)

Last checked: 3 November 2026 · How we check

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What it does

AI predicts machine faults
Estimate of remaining useful life
Automatic risk prioritisation
Connects sensors, historians and IoT
Scalable across thousands of assets
Early detection of fault signals
Shared knowledge base of fault patterns
Models machine behaviour automatically via AI

Comparable in industry & manufacturing

Operations1on requestTactoon requestRedokunProject Pass € 295 one-off (50.0…Maddox AIon requestAlmetra (voorheen Deltia)on requestAquasuiteon request
All 19 professional tools for industry & manufacturing
Underlying model

not public which language model is used; generative AI copilot (Maintenance Copilot) and time series foundation models for forecasting (according to provider); cloud SaaS on Azure and AWS, all data storage and processing in EU data centres, EU SCCs in supplier contracts (according to provider); ISO 27001 (LRQA), ISO 9001, CSA STAR Level 1, NIS2-compliant (according to provider); user messages are reused by generative AI on an opt-out basis (according to provider). Many tools build on a large model from, for example, OpenAI or Anthropic. If in doubt, ask for the data processing agreement: it states where your data goes.

GDPR check for industry & manufacturing

Questions about Senseye Predictive Maintenance

AI for industry & manufacturing
Which AI model does Senseye Predictive Maintenance use?
The maker of Senseye Predictive Maintenance does not make public which AI model sits underneath. Generative AI copilot (Maintenance Copilot) and time series foundation models for forecasting (according to provider); cloud SaaS on Azure and AWS, all data storage and processing in EU data centres, EU SCCs in supplier contracts (according to provider); ISO 27001 (LRQA), ISO 9001, CSA STAR Level 1, NIS2-compliant (according to provider); user messages are reused by generative AI on an opt-out basis (according to provider).
How much does Senseye Predictive Maintenance cost?
on request. Check the current price on the provider's website; rates change often.
Who is Senseye Predictive Maintenance for?
Senseye Predictive Maintenance is aimed at industry & manufacturing. It fits work such as predictive maintenance on machines, visual quality inspection, and creating work instructions and manuals.
What should I watch out for with AI in industry & manufacturing?
Production and process data is trade secret and sometimes subject to export controls. Check whether factory data leaves the premises and whether on-premise operation is possible.
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