• Production data locked in SCADA systems and operator panels that nothing else can read?

  • Running scheduled maintenance on equipment that has sensor data showing actual condition?

Industrial IoT Development

Industrial environments run on equipment that was built decades before IoT was a concept -- PLCs, SCADA systems, CNC machines, and process controllers that communicate over Modbus, OPC-UA, and proprietary protocols rather than modern APIs. Getting data out of that equipment and into systems where it can drive decisions requires a different approach than standard IoT.
We build industrial IoT software for manufacturing, energy, and process industries: SCADA integration, OPC-UA and Modbus protocol support, predictive maintenance data pipelines, and the MES and ERP integration that closes the loop between what your equipment is doing and what your business systems record.

  • OPC-UA, Modbus, and legacy industrial protocol integration alongside modern IoT

  • SCADA integration without disrupting existing operational technology

  • Predictive maintenance pipelines connecting sensor data to maintenance workflows

  • MES and ERP integration to close the loop between production and business data

Industrial IoT development connects manufacturing and process industry equipment -- PLCs, SCADA systems, CNC machines, and sensors -- to modern software platforms that make equipment data actionable. It involves integrating with industrial protocols like OPC-UA and Modbus, building data pipelines that bridge the OT-IT divide, and creating the dashboards, alerting, and predictive maintenance systems that production and maintenance teams rely on. The goal is turning equipment data into decisions: earlier maintenance interventions, faster fault diagnosis, and better production visibility.

Vodafone
Aldi
Nike
Microsoft
Heineken
Cisco
Calorgas
Energia Rewards
GE
Bank of America
T-Mobile
Valero
Techstars
East Ventures

The gap between what industrial equipment knows and what your business systems record is where production problems hide. Equipment showing early signs of bearing failure -- captured in vibration and temperature data -- while the maintenance system schedules the next inspection for next quarter. Production yield drifting below target while the MES records output counts but not the sensor readings that explain why.

Industrial IoT development closes that gap: connecting the OT layer (PLCs, SCADA, sensors) to the IT layer (MES, ERP, CMMS) in a way that lets production data drive operational and business decisions in real time, not at the end of a shift or the end of a week.

What we build

SCADA and OPC-UA integration

OPC-UA client integration for SCADA systems and modern industrial controllers: tag subscription, data change notification, and historical data read from OPC-UA servers. Address space browsing to identify available data points without requiring manual tag configuration. Secure channel setup with certificate-based authentication. Data forwarding to cloud or on-premise IoT platforms. Integration that respects OT network segmentation and does not require changes to the SCADA configuration or control logic.

Modbus and legacy industrial protocol support

Modbus TCP and Modbus RTU polling for legacy PLCs, drives, meters, and process controllers that predate OPC-UA. Register mapping, coil reading, and input register polling with configurable scan rates. Protocol gateway setup for equipment that uses proprietary industrial protocols -- converting to MQTT or HTTP for upstream processing. Data logger integration for equipment with no network interface, using hardware loggers attached to RS-485 or RS-232 buses.

Predictive maintenance data pipelines

Sensor data pipelines feeding predictive maintenance models: vibration analysis for bearing and motor health, temperature trend monitoring, pressure deviation detection, and energy consumption anomaly detection. Feature engineering from raw time-series sensor data into the inputs that maintenance models use. Integration with your CMMS so when a predictive alert fires, a work order is created automatically rather than requiring manual hand-off. Reduces emergency downtime by surfacing equipment degradation before it becomes failure.

Production monitoring dashboards

Real-time production dashboards for shift supervisors, plant managers, and operations teams: OEE (overall equipment effectiveness) tracking, production count vs target, cycle time monitoring, and downtime categorisation. Shift reports generated automatically from collected equipment data rather than manually compiled from operator logs. Historical trend analysis for identifying patterns across shifts, products, and equipment. Mobile-friendly views for supervisors who move between the office and the floor.

MES and ERP integration

Bidirectional integration between your IoT platform and your manufacturing execution system or ERP: production order data flowing from ERP into the IoT platform to provide context for equipment readings, and production actuals flowing back from equipment sensors to update ERP records without manual data entry. Work order creation in CMMS from equipment alerts. Quality data from visual inspection systems feeding into ERP quality management modules. The integration layer that removes the manual data reconciliation between production systems and business systems.

Edge processing for industrial environments

Edge computing for plant floor environments where cloud round-trips are too slow or connectivity is unreliable: local data collection, aggregation, and alerting on an industrial edge PC or gateway. Local operator interface running on the edge device for real-time status without cloud dependency. Store-and-forward to sync data to cloud systems when connectivity is available, with no data loss during outages. Designed for industrial temperature, vibration, and EMI environments with appropriate hardware selection and enclosure specifications.

Production data locked in SCADA systems that nothing else can read?

Tell us your equipment types, protocols, and the operational decisions you need to make from that data. We'll design the integration architecture and give you a fixed cost.

Talk about your industrial IoT project

  • AI Development -- predictive analytics and ML models for industrial sensor data

  • Cloud Migration -- cloud infrastructure for industrial data platforms

Frequently asked questions

SCADA integration depends on what the system exposes. Modern SCADA systems expose OPC-UA servers -- we connect an OPC-UA client that reads tags, subscribes to data changes, and forwards data to the IoT platform. Older systems often only support Modbus TCP or Modbus RTU -- we deploy a Modbus data collector that polls registers on a defined schedule and publishes data upstream. Where neither protocol is available, we use database replication (the SCADA historian database), screen scraping, or hardware data loggers attached to the equipment's communication bus. We assess each integration point during scoping and choose the least disruptive method that meets the data requirements.

OT (operational technology) is your production-critical equipment and control systems -- PLCs, SCADA, DCS, and the networks they run on. These systems are optimised for reliability and real-time control, not connectivity, and they often run on isolated networks for safety and security reasons. IT is your business systems -- ERP, MES, CMMS, and cloud infrastructure. Industrial IoT integration bridges the two layers: pulling data from OT systems through a secure integration point (data diode, DMZ, or managed gateway), processing and contextualising it, and making it available to IT systems that need it. The key constraint is that OT systems must not be put at risk by the integration -- we design the data flow so traffic moves from OT toward IT, not the other way around.

Most industrial environments don't have reliable internet connectivity on the plant floor -- and many use isolated OT networks by design. We address this with edge processing: an edge gateway or industrial PC on the plant floor runs the data collection, aggregation, and alerting logic locally. Results and summaries are synced to cloud systems when connectivity is available, and the edge system continues operating independently if the connection drops. Critical alerts can be delivered over local networks (to on-floor displays or local notification systems) without requiring cloud connectivity. We scope the edge vs cloud split based on your connectivity situation, latency requirements, and what decisions need to be made on the floor vs in a control room.

Industrial IoT projects typically run $40,000--$100,000 for a focused scope: one equipment type or production line, one or two protocol integrations, real-time dashboard, basic alerting, and integration with one downstream system (MES or CMMS). Broader deployments covering multiple production lines, multiple protocols, predictive maintenance pipelines, and full ERP integration run higher. Cost depends on the number of integration points, protocol complexity, edge vs cloud architecture requirements, and the number of systems the IoT platform needs to feed. We scope every project before pricing it.