Multi-technology perspective
Combine complementary inspection methods to see more than any single measurement can reveal.
Reliability engineering · Cypress, Texas
STAH combines industrial engineering with responsible AI and Machine Learning to help teams see problems earlier, understand equipment condition, reduce avoidable downtime, and build practical reliability programs.
Your uptime. Our focus.
AssessmentDiagnosticsAI and Machine LearningTrainingApplied AI and Machine Learning
STAH applies AI and Machine Learning where it can improve condition-data screening, pattern recognition, and prioritization—while keeping qualified people responsible for validation and action.
Explore condition intelligence with AI and Machine LearningConnect asset identity, sensor quality, operating state, process context, and maintenance history before modeling begins.
See the approach 02Use validated machine-learning methods to screen large datasets and surface unusual behavior for expert review.
See the approach 03Correlate vibration, thermal, electrical, ultrasound, oil, and process indicators instead of treating each signal in isolation.
See the approach 04Keep evidence, confidence, limits, overrides, and escalation visible to the people responsible for the equipment.
See the approachSTAH principle: Use AI and Machine Learning to narrow the search space. Engineers own the decision.
Condition assessment solutions
Build a targeted assessment or combine methods into an integrated condition strategy for electrical systems, rotating machines, motors, generators, and stationary assets.
PCAS
Integrated assessment for switchgear, transformers, and medium- and low-voltage assets.
Explore solutionMCAS
Condition insight for bearings, gearboxes, pumps, fans, compressors, and rotating equipment.
Explore solutionCCAM
Multi-technology evaluation of motors and generators across electrical and mechanical condition.
Explore solution24/7
Scalable monitoring strategies that help teams track change and act before functional failure.
Explore solutionField services
Use focused diagnostics or an integrated program to move from symptoms to equipment risk, recommended action, and follow-through.

Training & knowledge transfer
Practical training can be aligned to your assets, maintenance workflow, and reliability goals—from condition-monitoring fundamentals to responsible AI and Machine Learning.
Explore reliability training with AI and Machine LearningWhy STAH
Reliable information is valuable only when it helps people make a better next decision.
Combine complementary inspection methods to see more than any single measurement can reveal.
Turn field observations into prioritized actions maintenance and operations teams can use.
Plan each engagement around the operating environment, equipment boundaries, and site requirements.
Build internal capability through practical guidance, repeatable workflows, and focused training.
Selected customers
Organizations served across power, cement, oil and gas, and industrial operations.












Start a conversation
Share the asset, operating concern, data opportunity, or reliability goal. STAH can help shape a focused, human-reviewed next step.