Senseye
A Siemens Company. The Art of the Unplanned.
Overview
Senseye, now part of Siemens, provides a cloud-based software platform for predictive maintenance. It uses machine learning algorithms to automatically forecast machine failure and estimate the remaining useful life of industrial assets. The solution is designed to be scalable and is used by major manufacturers to reduce unplanned downtime and increase maintenance efficiency without requiring data science expertise from the user.
✨ Key Features
- Automated Condition Monitoring
- Remaining Useful Life (RUL) Forecasting
- Attention Engine for prioritizing assets
- Root Cause Analysis
- Integration with CMMS and IoT platforms
- Scalable Cloud Architecture
🎯 Key Differentiators
- Designed for large-scale deployments across many assets
- Automated, proprietary machine learning that requires no data scientists
- Integration into the Siemens industrial ecosystem
Unique Value: Provides a turnkey, scalable software solution that automates predictive maintenance, allowing large manufacturers to reduce downtime at scale without needing to build an in-house data science team.
🎯 Use Cases (5)
✅ Best For
- Scaling predictive maintenance across hundreds or thousands of assets
- Automating failure detection for rotating equipment
- Integrating PdM insights into existing maintenance workflows
💡 Check With Vendor
Verify these considerations match your specific requirements:
- Companies with only a handful of assets to monitor
- Organizations looking for a hardware-inclusive solution
🏆 Alternatives
Offers a more automated and user-friendly approach to PdM than generic data science platforms, and is more scalable as a pure software solution compared to hardware-centric providers.
💻 Platforms
🔌 Integrations
🛟 Support Options
- ✓ Email Support
- ✓ Phone Support
- ✓ Dedicated Support (All tier)
🔒 Compliance & Security
💰 Pricing
✓ 14-day free trial
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