About Samotics
We turned electrical signals into an industrial monitoring layer.
Samotics was founded in 2015 to solve a structural blind spot in condition monitoring: critical motor-driven assets that are submerged, enclosed, remote, hazardous, or too numerous to instrument one by one. SAM4 reads current and voltage at the motor control cabinet and turns them into validated asset intelligence for industrial teams worldwide.
ESA was known science. Samotics made it work at scale.
Electrical Signature Analysis was established long before Samotics. The hard part was turning it into a production system: noisy cabinets, variable loads, VFDs, remote assets, incomplete asset data, and maintenance teams that need clear recommendations instead of more plots. Samotics was built to solve that full industrial problem.
The signal
Motor current and voltage contain measurable evidence of electrical, mechanical, and process faults. The physics was established. The missing piece was a system that could use it across real industrial fleets.
The production system
We built the acquisition hardware, signal conditioning, fault models, baselining, validation workflow, and deployment stack needed to run ESA continuously in noisy industrial environments.
The infrastructure
SAM4 now monitors 7,000+ assets across water, chemicals, oil and gas, metals, airports, and manufacturing. ABB embedded Samotics ESA into its ACS880 drive portfolio. Cabinet-based monitoring is now industrial infrastructure.
The constraint we chose to solve
Most condition monitoring depends on getting close to the machine. That leaves a structural blind spot: assets that are submerged, enclosed, hazardous, remote, or too numerous to instrument one by one.
Read the full Monitoring Blind Spot thesis →Turning ESA into a production system took more than signal processing.
The physics matters. But production reliability requires the full stack: safe installation, high-resolution acquisition, clean signal handling, asset-fit scoping, robust models, expert validation, customer workflow, and integration into maintenance systems. That is what Samotics built.
The signal problem
Three-phase current and voltage at the MCC carry useful fault evidence. They also carry noise: VFD harmonics, load variation, power-quality effects, wet-weather operating changes, and every other electrical artefact in the plant.
SAM4 needed acquisition hardware, signal conditioning, edge sampling, and analytics tuned for fault-signature extraction in real cabinets, not lab signals.
The fit problem
ESA works best when the fault mechanism affects current, voltage, torque, speed, load, or electromagnetic balance strongly enough to be seen.
Every deployment needs scoping: asset type, operating regime, signal path, motor configuration, available asset data, and expected failure modes. SAM4 is powerful, but it is not a universal plug-and-play detector for every asset and every fault.
The trust problem
A spectrum is not a maintenance decision. Customers need to know what changed, where to look, how urgent it is, and what evidence supports the call.
SAM4 combines automated detection with reliability-engineer review for ambiguous, urgent, or edge-case findings. The output is a validated recommendation with evidence, severity, and next action, not another unexplained plot.
The adoption problem
A detection that stays in a separate dashboard does not change maintenance behaviour. SAM4 has to fit into how industrial teams already work: CMMS, reports, dashboards, site routines, shutdown planning, and internal proof of value.
SAM4 includes onboarding, asset mapping, workflow integration, customer feedback loops, and evidence that helps teams decide where to act next.
The scale problem
Fleet-scale ESA requires more than one customer model. SAM4 learns from thousands of monitored assets, labelled outcomes, false alerts, confirmed faults, resolved work orders, and asset-specific baselines.
The advantage compounds when shared field learning and local operating context work together.
Built for the blind spot in industrial reliability.
SAM4 is designed for three-phase motor-driven assets where asset-mounted monitoring is hard to deploy, too intermittent, or too costly to scale. It measures current and voltage at the motor control cabinet, analyses the electrical signature, validates the finding, and delivers a maintenance recommendation your team can act on.
Fit matters. Detection confidence varies by asset type, operating regime, and failure mode. We scope every fleet before rollout and publish performance by asset type where the evidence base supports it.
The cabinet is becoming a monitoring point.
SAM4 sits where electrical infrastructure, asset reliability, and operational data meet. That makes cabinet-based monitoring relevant not only to maintenance teams, but also to automation partners, system integrators, and industrial infrastructure providers.
ABB Motion
ABB Motion embedded Samotics ESA into its ACS880 drive portfolio. For compatible drives, the current and voltage signal can already be measured by the drive; SAM4 adds the analytics, validation, and maintenance workflow layer.
Why it mattersCabinet-based monitoring can become part of the drive and electrical infrastructure customers already use.
European Investment Bank
The European Investment Bank supported Samotics' expansion because cabinet-based monitoring can improve reliability and energy efficiency across critical industrial assets.
Why it mattersContinuous asset intelligence is moving from software add-on to infrastructure layer.
Partnerships matter because this category does not live only in a dashboard. It has to fit into the electrical, maintenance, and data infrastructure of industrial sites.
Samotics leadership team
Built by engineers and operators with deep expertise in electrical systems, AI, and industrial reliability.
Jasper Hoogeweegen
Leads strategy and investor relations. Former CFO, CCO, and CSO at Coolblue. Started in strategy consulting at Bain.
Simon Jagers
Leads commercial growth and strategic partnerships. Former enterprise sales leadership at Dell, Oracle, and EMC.
Gerben Gooijers
Built the ESA detection engine and SAM4 hardware platform from scratch. Former Partner and CIO at Optiver.
Erik Gaarenstroom
Runs operations, delivery, and customer success across five continents. Former consultant at Bain. INSEAD MBA.
Hans van den Heuvel
Manages finance, governance, and investor relations. Former Transaction Services at KPMG.
Thijs Bootsma
Leads product strategy, roadmap, and the SAM4 platform experience. Former consultant at Bain.
Advisors
Jeroen van der Veer
Former CEO of Royal Dutch Shell. Former Chairman of Philips. Strategic counsel on energy sector positioning and enterprise governance.
Dr. Johan Paulides
CEO of AE-Group. Former researcher in electric motor technology at Eindhoven University of Technology. Technical advisory on ESA signal physics and fault detection methodology.
How we work when asset decisions matter.
We work best with industrial teams that need clear evidence, honest boundaries, and practical recommendations they can act on. No black box. No inflated claims. No handoff to someone who cannot answer technical questions.
We focus on consequential assets
SAM4 is built for assets where failure creates real cost: downtime, safety risk, environmental impact, energy waste, or high maintenance burden.
If the asset is not a strong fit, or the expected value is too low, we will say so.
We say what the data supports
Every recommendation should make clear what we detected, what evidence supports it, how confident we are, and what action we recommend.
We publish boundaries, methodology notes, and asset-specific detection data because trust depends on precision.
We stay close after deployment
Condition monitoring only creates value when it changes maintenance decisions. Our reliability engineers support onboarding, review ambiguous findings, explain alerts, and help your team close the loop after inspection or repair.
The goal is not more dashboards. The goal is better decisions in your workflow.
From validated monitoring to an asset-level data layer.
SAM4 started with condition monitoring: detect developing faults early, validate the finding, and help maintenance teams act before failure. The same current and voltage signal can do more. It can show how assets run, how much energy they use, how load changes, where abnormal operation starts, and which assets need attention first. Our direction is simple: make cabinet-based asset data useful wherever industrial teams already work, in maintenance workflows, energy programmes, digital twins, data platforms, and operational dashboards.
Validated condition monitoring
SAM4 detects developing faults, validates customer-facing findings, and sends maintenance teams clear actions: what is wrong, where to look, how urgent it is, and what evidence supports the call.
Fewer unplanned failures, better planning, more confidence in hard-to-reach assets.
Asset-level data in customer systems
Condition, energy, performance, and operational data flowing into CMMS, historians, dashboards, digital twins, and sustainability platforms.
Better data where customers already make decisions, not another dashboard.
Cabinet-based monitoring as industrial infrastructure
As industrial systems become more data-driven, they need trusted asset-level inputs. SAM4 provides those from the cabinet: current, voltage, condition, load, runtime, energy, and performance evidence.
Every better decision starts with better asset data.
SAM4 will keep doing what customers value most, making invisible assets visible, while making the data easier to use in the systems, models, and workflows they already trust.
Three ways to work with Samotics.
Evaluate SAM4 for your assets. Join the team building it. Partner with us to bring cabinet-based monitoring into industrial infrastructure.
Reliability or operations team
Review where SAM4 fits your fleet. In 30 minutes, we look at your asset types, access constraints, failure history, and maintenance priorities to identify where cabinet-based monitoring is likely to create value.
Book an asset-fit review →Engineer, data scientist, or operator
Help build the monitoring layer for assets that are hard to reach. We hire across signal processing, machine learning, electrical engineering, reliability, product, and customer operations.
View open roles →OEM, system integrator, or service provider
Add cabinet-based condition, energy, and operational intelligence to your customer offering. We support technical enablement, co-selling, integrations, and deployment models.
Discuss partnership →