Revolutionize Predictive Maintenance
with Xpdeep Actionable AI
Cut sensor costs, simplify compute, and act before failure — with fully explainable, certifiable deep models.
Why AI Struggles in Predictive Maintenance
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Most AI models are black boxes — hard to trust, certify, or act on
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Excessive sensor and compute needs make them hard to scale
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They only predict — without offering concrete operational advice
"What's the use of predicting a failure
if you can't prevent it?"
Xpdeep Makes Predictive Maintenance Truly Actionable
Xpdeep enables you to design and deploy deep models that are:
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Understandable: Fully explainable at every step
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Efficient: Minimal sensors and low compute load
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Actionable: Suggest concrete steps to delay or avoid failures
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Certifiable: Ready for regulated, mission-critical use
Scania Case Study: Fewer Sensors, Better Performance
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–82% sensors needed (from 106 to 19)
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–50% inference compute
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–33% model size
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+ Real-time actionability: Prescribes operating changes to avoid failure
Built for Real-World Deployment
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Certifiable and auditable models (AI Act, ISO, MIL-STD…)
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Compatible with your existing MLOps and PyTorch stack
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ROI through lower sensor and compute costs, and reduced downtime
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Domain expert–friendly: Full transparency and control
Simulate. Recommend. Adjust.
Xpdeep's built-in analysis enables models to:
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Simulate failure scenarios
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Recommend optimal usage to delay issues
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Empower maintenance teams with specific, risk-aware decisions
The First Fully Integrated Framework for Actionable Deep Learning
- Explainability by design — not post-hoc
- Models built to be trusted, certified, and deployed
- Insights aligned with operational goals
- All-in-one: Design, optimize, simulate, explain, and act