Cabinet-based condition monitoring system
From cabinet measurement to validated work order.
SAM4 combines MCC-installed hardware, Electrical Signature Analysis, reliability-engineer review, and workflow integration. It monitors AC-motor-driven assets by turning current and voltage into validated findings across electrical, mechanical, drivetrain, and hydraulic load-path faults. Each finding includes likely fault type, severity, evidence, and a recommended next action.
What is SAM4?
An end-to-end monitoring system - SAM4 combines cabinet-installed hardware, cloud analytics, a managed monitoring service, and workflow integrations into a single monitoring solution. Data acquisition hardware captures current and voltage waveforms at the motor control cabinet. The gateway pre-processes the signal into failure indicators locally, which makes SAM4 viable on satellite-only and low-bandwidth sites. The reduced dataset is sent to the cloud, where analytics run on every measurement. Reliability engineers review ambiguous and edge-case detections before they reach your team. Validated alerts flow into your dashboard, your inbox, or directly into your CMMS as structured work orders.
SAM4 works alongside vibration systems, SCADA, and maintenance planning tools. Nothing gets replaced. SAM4 closes the monitoring blind spot around AC-motor-driven assets where mounted sensors are impractical, unsafe, or too expensive to maintain.
Architecture from the cabinet to the cloud
SAM4 hardware sits in the MCC and captures current and voltage. Waveform data flows to Samotics analytics. Reliability engineers validate ambiguous findings. Confirmed alerts return to your dashboard, inbox, or CMMS as structured work orders.
What your team sees
SAM4 gives reliability, maintenance, and operations teams a shared view of asset condition. Start with fleet-level risk, drill into asset health, review the incident evidence, and track energy performance from the same system.
One view across sites, asset types, and health states. Drill from fleet to signal in two clicks.
From motor current to a validated work order
Most systems raise alerts. SAM4 carries each finding further: from raw measurement to diagnosis, expert review, recommended action, and CMMS-ready work order.
SAM4 does not stop at anomaly detection. It captures the electrical signal from the cabinet, identifies likely faults, validates the finding, and sends your team a clear maintenance action.
Measure
SAM4 captures current and voltage at the motor control cabinet. Three-phase waveforms are converted into the frequency domain.
You get: a high-resolution electrical signature for every monitored asset.
Detect
Models compare each asset against its own healthy baseline and known fault patterns from the monitored fleet.
You get: a flagged deviation with an initial fault hypothesis.
Diagnose
SAM4 identifies the likely fault type, drivetrain location, confidence, severity, and supporting spectral evidence.
You get: a diagnostic record your team can review.
Validate
Reliability engineers review ambiguous and edge-case findings before the customer is notified. Post-review false-alert rate: 2.1%.
You get: a validated alert, not a raw anomaly.
Recommend
Each alert includes a specific next step: inspect, schedule maintenance, escalate, or watch.
You get: a recommended action and timeframe.
Integrate
Validated alerts route into your CMMS, email, dashboard, or workflow tool. Resolution data feeds back into the model.
You get: a work order in your existing maintenance flow.
The result: your team gets fault evidence, severity, and a recommended action before failure, without installing sensors on the machine.
Validated before it reaches your team
SAM4 combines continuous AI detection with expert validation. SAM4 monitors connected assets continuously while they operate, building context from runtime, load, and signal history. Reliability engineers review ambiguous and high-impact findings before they become customer-facing alerts.
Your team does not receive a dashboard full of unexplained anomalies. You receive validated alerts with fault evidence, severity, and a recommended next step.
Your alerts are reviewed by engineers trained in electrical signature analysis, bearing diagnostics, and drivetrain failure modes. They work across three regions to provide follow-the-sun coverage. SAM4 flags potential faults continuously; engineers review ambiguous and edge-case detections, escalate the urgent, and filter noise before alerts reach your team.
Every reviewed alert improves the system. Validated faults, false alerts, customer confirmations, and resolved work orders feed back into SAM4's models and monitoring process. The dataset compounds across 7,000+ monitored assets and 80+ customers. The 2.1% post-review false-alert rate is calculated across 1,402 customer-facing detected and false-alert outcomes in the last 12 months.
SAM4 monitoring is distributed across Europe, Asia, and the Americas. When an urgent finding appears outside local working hours, the active monitoring region reviews and escalates it before the customer's next shift starts.
Trained in electrical signature analysis, motor diagnostics, drivetrain fault patterns, and load-path behaviour, the same engineers who train SAM4's detection models review your alerts.
Four checks before rollout
Before SAM4 goes live, we scope four things: the asset, the cabinet, the data path, and your maintenance workflow. That makes deployment predictable before hardware is installed.
Installation fit
< 60 minutes
to install per motor at the MCC
Split-core CTs and voltage taps are installed in the motor control cabinet. No asset-mounted sensors and no routine entry into wet, hazardous, or hard-to-reach areas.
Monitoring fit
Per-fleet scoping
asset, motor, drive, load, and failure modes reviewed
SAM4 is scoped against asset type, motor configuration, drive setup, operating profile, load stability, signal quality, and the fault modes you need to detect across direct electrical, drivetrain, and process or hydraulic load-path faults. Most three-phase induction motors above 1 kW are technically suitable, including many VFD-driven assets. Each fleet is reviewed before deployment.
Connection & workflow
SAP · Maximo · Infor
CMMS systems, native integration
SAM4 connects to the platform over a cellular path outside your IT/OT network. Validated findings push as structured work orders with fault type, severity, asset ID, evidence, and recommended action. No duplicate data entry.
Security review
ISO 27001 · 9001
independently audited by DNV
SAM4 uses a secure data path outside your IT/OT network. Data is encrypted in transit and at rest. Documentation is available for IT, security, procurement, and NIS2-aligned critical infrastructure reviews.
Start small. Prove value. Scale with confidence.
Most customers begin with 10 to 25 critical assets, prove value on site, then expand across assets and locations.
The first deployment is designed to build internal proof. You select assets where monitoring is difficult, failure is costly, or vibration access is impractical. SAM4 installs at the motor control cabinet, baselines normal behaviour, validates early findings, and gives your team evidence for the next rollout phase.
Choose the right first assets
Start with 10 to 25 critical motors or driven assets. Prioritise equipment with high downtime cost, poor monitoring coverage, repeated failures, or limited physical access.
Install without machine access
SAM4 installs at the motor control cabinet, usually in under 60 minutes per asset. No asset-mounted sensors. No routine access to wet, hazardous, submerged, or enclosed equipment.
Build proof from validated alerts
SAM4 baselines normal behaviour, detects developing faults, and validates ambiguous findings before notifying your team. Each alert includes fault evidence, severity, and a recommended next step.
Scale the same model
Once the first sites prove value, expand across assets, sites, and regions. The same platform, monitoring team, and workflow integrations scale with you.
Field evidence, not lab claims
SAM4 is validated across real industrial fleets, customer-confirmed faults, and operational outcomes.
7,000+ monitored assets. 80+ customers.
SAM4 monitors rotating assets across water and wastewater, chemicals, oil and gas, metals and mining, pulp and paper, airports, and manufacturing.
Why it matters: the models learn from real operating conditions across diverse industries, not isolated lab tests.
95.5% recall on confirmed real conditions.
Recall measures how many confirmed real conditions SAM4 detected in time. Calculated from 1,467 scored incidents on core rotating assets, 12 months ending 1 May 2026. Post-review false-alert rate: 2.1%. Reviewed quarterly.
Why it matters: high recall means fewer faults slip through. A low false-alert rate means your team can trust the system.
£10M+ reported benefit at Yorkshire Water.
Yorkshire Water's internal analysis reports more than £10M in benefit across their SAM4 deployment. Customer since 2021.
DuPont
“At first I was a bit sceptical about SAM4's ability to detect failures by analysing electrical waveforms, but the results speak for themselves: it just works.”
Schiphol Airport
“SAM4 detected possible bearing damage to the gearbox motor, which we had not picked up through our vibration monitoring. Following the SAM4 alert, we found that the bearing had already degraded significantly. SAM4 had saved us from a costly unexpected failure.”
Yorkshire Water
“Critical in our monitoring of hard to reach assets such as submersible pumps. System works very well, support is also very good.”
— Michael Horner
Start here
Begin with your most critical assets. Most customers start with 10 to 25 assets. Build confidence, then expand across more of the rotating assets your current monitoring programme does not cover.