Utilities · Manufacturing
Energy-Smart Industrial Systems
Sensors measure machine energy consumption, predict peak load, and track carbon footprint. AI agents shift flexible workloads to cheap or renewable energy windows automatically, instead of running everything on a flat schedule regardless of price or grid conditions.
Energy cost is now a real-time signal, not a monthly bill
Industrial and commercial electricity tariffs increasingly move in real time — day-ahead and even five-minute pricing, demand-response events, and time-of-use windows that shift with renewable generation. A facility that only looks at energy cost once a month has no way to act on any of that. A facility that can shift a flexible load — a batch process, a cold-storage compressor cycle, a non-time-critical compute job — into a cheaper or cleaner window can turn a pricing signal into real savings, but only if the systems making that decision see the signal and the machine state at the same time.
How Relay fits
Relay ingests machine-level power telemetry alongside the process data that determines whether a load is actually flexible right now — a compressor can shift its cycle if the cold store is within its temperature band, a batch process can delay a step if it's not on the critical path. An agent consuming both streams over Relay's native protocol support can make that shift decision locally, in the same sub-millisecond latency budget as any other control-loop decision, rather than waiting on a cloud-hosted optimizer that may or may not be reachable when the decision needs to be made.
- →Native protocol support: pull power telemetry directly from Modbus and OPC UA meters and drives, without a separate energy-monitoring integration layer.
- →Stream processing built in: combine live price signals with machine state using Relay's SQL-based rules, without standing up a separate stream-processing service.
- →Edge-resident decisions: load-shifting logic runs on-site, so it keeps working even if the connection to a corporate energy-management platform is down.
Where this applies
Utilities balancing distributed generation and demand response, and manufacturers with flexible, non-time-critical loads, are the clearest fits. Both share the same requirement: an accurate, real-time view of machine and process state, correlated against an external price or carbon signal, feeding a decision that has to happen locally and fast enough to matter.
See it against your own architecture
Every protocol and transport on this page is available on the Free plan. Run it on your own hardware before you talk to anyone.