Energy & Utilities

Reliability and field operations, built on connected data.

Asset analytics, field workflows and customer platforms across generation, network and retail operations.

How this sector runs

Where the work starts, and where it is decided

Every sector has a different shape. The node in gold is the decision the whole flow turns on — it is rarely in the same place twice.

Assets are distributed, long-lived and expensive to visit. The work is turning telemetry into a dispatch decision before a fault becomes an outage.

Sector pressures

These are the constraints we most often find when we start work in this sector.

Ageing asset base
Infrastructure operating beyond design life, where condition monitoring is the difference between planned and unplanned intervention.
Grid complexity
Distributed generation and bidirectional flow on networks designed for neither.
Field workforce
Dispersed field operations where scheduling and information access determine productivity.
Regulatory reporting
Performance, outage and environmental reporting obligations with strict data requirements.
Customer expectation
Consumer-grade digital service expected from a traditionally infrastructure-led sector.

Use cases

Asset condition analytics
Condition monitoring and intervention planning across a distributed asset base.
Outage management
Detection, prediction and restoration coordination.
Field workforce enablement
Mobile access to asset, work order and safety information.
Customer portals
Usage, billing and service self-service.
Operational data platform
Sensor, SCADA and enterprise data brought together for analysis.

Every connection below is recorded in the content itself, and each one says why it is here.

Open the guided finder with this sector already selected. Four questions, and an explanation of why each capability came up.

Start from a goal

Questions

How do you bring SCADA data into an enterprise analytics platform safely?: Through a unidirectional boundary wherever the use case allows. Operational data flows outward to the analytics platform; control commands do not flow back through the same path. Combined with network segmentation and protocol-aware gateways, this gives analytical value without creating a control-plane exposure.
What does condition-based maintenance require beyond sensors?: Failure history with enough labeling quality to learn from, a maintenance planning process capable of acting on a prediction, and a clear decision on the cost of a false positive versus a missed failure. The sensors are usually the easiest part.

Tell us what you are trying to change and we will connect you with people who have worked on that specific problem.