Industry experience

Different sectors. Different proof.

The architecture must reflect how each environment controls quality, availability, lifecycle and change.

Aerospace and defence

Preserve evidence across long product lifecycles.

Connect assembly tools, equipment, MES, PLM and quality systems while maintaining product genealogy and controlled configuration.

Core issues: Legacy machines, serial traceability, tightening evidence, configuration and multi-system ownership.
Strong use cases: Connected tools, digital work instructions, machine genealogy and quality event integration.
Website proof: Architecture diagrams, acceptance logic, documented recovery and anonymized program constraints.

Manufacturing

Industrialize machine connectivity, paperless execution, traceability and asset performance across lines and sites.

Core issues: Manual data entry, proprietary protocols, poor line visibility, OEE context and fragile point-to-point interfaces.
Strong use cases: IIoT connectivity, digital shopfloor, asset optimization, predictive maintenance and ERP/MES integration.
Website proof: Repeatable deployment patterns, operator workflows and supportable system ownership.

Smart cities

Connect transport, utilities and municipal assets while keeping asset identity, ownership, condition and field recovery explicit.

Core issues: Distributed vendors, intermittent connectivity, asset tracking, field maintenance and inconsistent telemetry.
Strong use cases: Fleet management, remote monitoring, alarms, asset performance and infrastructure maintenance.
Website proof: Edge-to-platform architecture, state management and field-support procedures.

Electronics and battery manufacturing

Contextualize high-volume quality and time-series data across fast-changing equipment and supplier landscapes.

Core issues: Equipment genealogy, parameter traceability, vendor diversity, data volume and rapid production scale-up.
Strong use cases: Quality parameter capture, time-series analysis, digital thread and scalable machine onboarding.
Website proof: Canonical data models, line templates and source-to-consumer validation.

Food, beverage and process manufacturing

Bring process signals together with production, quality and business systems so teams can act during the batch, not after it.

Core issues: Batch tracking, environmental data, energy monitoring, downtime and manual quality checks.
Strong use cases: Batch event integration, condition monitoring, utility dashboards and digital quality workflows.
Website proof: Timestamp handling, data quality rules and traceable exception workflows.

Energy, utilities and industrial infrastructure

Connect legacy and modern assets for monitoring, maintenance and time-series analysis across large physical estates.

Core issues: Distributed assets, remote monitoring, legacy protocols, maintenance history and inconsistent state.
Strong use cases: Asset performance management, predictive maintenance, fleet visibility and alarm contextualization.
Website proof: Connectivity resilience, stale-state detection, buffering and operational recovery.

A strong integration begins by defining acceptable evidence, lifecycle, operating state and ownership.

What must be linked to serial, batch, operation, tool and asset?

How are live, degraded, stale and disconnected states communicated?

How long must interfaces, identifiers and records remain understandable?

Who detects, investigates and recovers when the data flow fails?

Bring the sector constraints, current systems and one process that needs to work better.