Our Services

Four services,
measurable results

From sensor connectivity to AI models in production — we cover your complete industrial digital transformation journey with local presence in Guadalajara.

Flagship Service

Predictive Maintenance (PdM)

Our flagship product. We combine IoT sensors, vibration/temperature/current analysis and machine learning models to predict equipment failures before they occur — reducing unplanned downtime up to 40%.

  • Vibration, temperature and current spectral analysis
  • ML models trained on your specific equipment
  • Real-time alerts with remaining useful life (RUL) estimates
  • MODBUS, OPC-UA and MQTT protocol compatibility
  • Edge deployment or cloud (Azure / AWS)
  • 90-day pilot with guaranteed ROI metrics
Request PdM Pilot
Case Study
38%
Unplanned downtime reduction at an automotive plant

A Tier 1 automotive supplier in Jalisco was experiencing recurring compressor failures causing 8–12 hours of unplanned downtime per month. After deploying our PdM pilot on their critical assets:


Before: 3–4 unplanned stoppages/month · Avg. 10 hrs downtime each · Reactive maintenance model


After 90 days: 1 stoppage/month · Alerts issued 7–14 days before failure · Maintenance scheduled during planned windows


Annual savings: MXN 3.8M in reactive maintenance costs + production loss avoided

Industrial AI

Industrial Artificial Intelligence

Beyond predictive maintenance, we deploy custom AI models across manufacturing operations: visual quality inspection, process optimization, demand forecasting and anomaly detection — at the edge or in the cloud.

  • Computer vision quality inspection (defect detection)
  • Anomaly detection models for process streams
  • Production yield and demand forecasting
  • Process parameter optimization with reinforcement learning
  • Edge inference (Jetson, Raspberry, industrial gateways)
Discuss Your AI Project
Case Study
99.1%
Anomaly detection accuracy in discrete manufacturing

A discrete manufacturer in the Guadalajara metro area needed a quality inspection solution for a high-volume assembly line where manual visual inspection was the primary method.


Solution deployed: Computer vision model on industrial camera + edge inference gateway · 0 cloud dependency


Results: 99.1% detection accuracy · 3× faster than manual inspection · 62% reduction in defective parts reaching final assembly

Industrial IIoT

Industrial IoT Connectivity

Before AI can work, your machines need to talk. We design and deploy the sensor networks, communication protocols and data pipelines that feed your AI and monitoring systems.

  • MODBUS RTU/TCP, OPC-UA, MQTT, Profibus integration
  • Industrial sensor selection and installation
  • Edge gateways + historian configuration
  • Azure IoT Hub, InfluxDB, Grafana dashboards
  • OT/IT network security architecture
  • Real-time monitoring dashboards for plant managers
Assess Your Connectivity
Case Study
6 wks
Full IIoT pilot deployed at a food & beverage plant

A CDMX-based food company had zero real-time visibility into their cold-chain and production equipment. Legacy PLCs had no connectivity to modern systems.


Deployed in 6 weeks: 48 sensors · OPC-UA bridge to SCADA · InfluxDB + Grafana dashboards for plant floor and management


Outcome: First company-wide real-time asset visibility · Foundation for PdM deployment in Phase 2

Digital Transformation

Industry 4.0 Consulting

Not every manufacturer knows where to start with digital transformation. We provide the roadmap, change management, and technical execution to move from reactive operations to a data-driven, AI-augmented plant.

  • Digital maturity assessment (Industry 4.0 framework)
  • 3-year technology roadmap with phased investment
  • MES / ERP integration strategy
  • Organizational change management and team training
  • KPI definition and OEE / MTBF / MTTR baseline
  • Executive reporting and board-level ROI communication
Request Assessment
Case Study
MXN 4.2M
Annual savings in reactive maintenance — Chemical plant, GDL

A chemical manufacturer in the Guadalajara metro was spending heavily on reactive maintenance with no visibility into asset health. We deployed a full Industry 4.0 roadmap starting with a digital maturity assessment.


Phase 1 (3 months): IIoT connectivity for 12 critical assets · KPI baseline established


Phase 2 (6 months): PdM deployed · Maintenance team retrained · Reactive maintenance budget reallocated


Year 1 result: MXN 4.2M saved · OEE improved 11 points

Industrial Infrastructure

Instrumentation & Electrical (I&E)

Before any AI model can predict a failure, your assets need to speak. We design, install, and commission the instrumentation and electrical infrastructure that converts physical signals into actionable data — with NOM-001-SEDE-2012, ISA, and IEC compliance built in from day one.

  • CENAM-traceable calibration — eliminating false alarms and bad data in AI models
  • PLC / SCADA / HMI: Siemens, Allen-Bradley, Schneider — native OPC-UA integration
  • Complete electrical installation compliant with NOM-001-SEDE-2012
  • Instrumentation asset management with RCM methodology
  • Safety Instrumented Systems (SIS) per IEC 61511 / ISA 84 for critical processes
  • Technical training in-plant or at our Guadalajara training center

Standards & norms

NOM-001-SEDE-2012 ISA 5.1 / ISA 84 IEC 61511 IEC 60079 CENAM IEC 62443
View I&E Services
The starting point
I&E → AI

The infrastructure that makes predictive maintenance possible

Most Industrial AI projects fail not because of the algorithm — but because field data is unreliable. I&E is the layer that guarantees trustworthy signals: calibrated, continuous, and connected to your digital systems.

±0.075%
Accuracy required for reliable AI
6 services
From engineering to training

Not sure which service fits your plant?

Let's do a free 30-minute diagnostic call. We'll identify your biggest operational pain points and recommend the right starting point — no commitment required.