Conversational AI · Condition Monitoring

Hire your world-leading
engineer. For the
price of software.

MachineVibe.AI wraps a physics-informed diagnostic engine in a smart language model - drawing on your sensor data, past work orders, and engineering documents to deliver fast, accurate and automated condition assessments.

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The Problem

All available approaches force you to choose between cost and trust.

Machine condition monitoring can be addressed by human experts or automated with AI. Both routes work in theory. In practice, each comes with drawbacks serious enough to make industrial-scale deployment impractical.

01 · Human Experts

Expensive and prone to error

Specialists bring real expertise, but they are costly, slow, and fallible. Human performance degrades under fatigue, and availability never scales.

  • Expensive to hire, retain, and deploy on-site
  • Prone to error under fatigue and time pressure
  • Cannot scale across many machines simultaneously

02 · Standard AI

Untrustworthy and data-hungry

Generic ML models offer automation but cannot be trusted in safety-critical settings. They require vast labelled datasets and give no explanation for their outputs.

  • Black-box outputs no engineer can verify
  • Requires large labelled datasets rarely available in practice
  • Poor generalisation across machines and environments
Our Approach

No compromise on depth, trust or accuracy.

Mimics world-leading expert workflows. Automatically applies order tracking, kurtogram analysis, envelope spectrum, harmonic screening, and ISO limits in the correct sequence.
Fully interpretable and explainable. Every decision is grounded in signal-processing theory and can be traced back to physics. No black-box outputs.
Uses the most state-of-the-art analytical methods. From physics-informed neural networks to cyclostationary analysis, always applying the right tool for the right problem.
Reads work orders and past reports. Integrates historical maintenance data and engineering documents to produce context-aware recommendations.
Analyses full datasets and builds condition trends. Detects developing faults early across entire monitoring histories, not just single snapshots.
Writes structured diagnostic reports automatically. Professional PDF reports with plots, severity assessments, and ranked maintenance recommendations.
Interacts conversationally to explain every action. Ask follow-up questions, challenge a finding, or request deeper analysis. Just like working with a real engineer.
24/7 availability, zero fatigue, no human errors. Consistent expert-level assessments at any scale, for the cost of software. Hire your world-class engineer today.
Why MachineVibe.AI?

Proven concept.
Ready to deploy.

MachineVibe.AI is built by researchers at the intersection of signal processing, mechanical engineering, and applied AI. The underlying approach is scientifically validated and ready for real-world deployment.

Published in Mechanical Systems and Signal Processing Peer-reviewed and independently validated in the world's leading journal for condition monitoring signal processing.
5+ years of specialised expertise Deep domain knowledge in vibration analysis and physics-informed neural networks, built for industry not repurposed from general AI.
Validated on real-world benchmark data The system outperforms current deep learning alternatives on independent benchmarks and is ready for deployment in real industrial settings.
Get Started

Ready to modernise your
condition monitoring?

Whether you want a live demo, a technical deep-dive, or just want to understand if MachineVibe.AI is right for your use case. We would love to hear from you.

info@machinevibe.ai

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