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PERYX.AI

Utilities & Grid

In discussion

Asset health from the data you already collect.

Transmission and distribution assets, load behaviour, and network health.

The operating problem
  1. 01

    SCADA and metering produce enormous volumes of data that are used for control and settlement, then archived without ever being interpreted.

  2. 02

    Maintenance is scheduled by age and inspection cycle rather than by observed condition.

  3. 03

    Alarm volume exceeds what any control room can triage, so operators filter by habit rather than by consequence.

How Peryx applies
  1. 01

    Existing SCADA, metering, and event history are ingested at native resolution without new instrumentation.

  2. 02

    Asset classes are modeled against expected electrical and thermal behaviour under observed loading.

  3. 03

    Deviations are ranked by consequence, so the queue reflects risk rather than alarm count.

Under the hood

The pipeline does not change between sectors.

Only the physics model in the middle is sector-specific. That is the whole argument for expanding beyond solar.

  1. Sensors

  2. Telemetry

  3. Physics model

  4. Digital twin

  5. Insights

  6. Recommendations

  7. Decisions

Where we actually are
In discussionIn active deployment conversations with operators.

In active discussion with network operators, working from existing SCADA and metering data.

Solar is the sector where this architecture has been proven against real operational data. If you operate utilities & grid assets and want to know whether it transfers to yours, the honest answer comes from looking at your data together — not from a page like this one.

Related productAvailable today

Solar Intelligence Platform

Physics-calibrated performance intelligence for solar fleets — every megawatt-hour of loss attributed to a cause.

See the platform

Bring your hardest question.

Mixed vendors, sparse instrumentation, an anomaly nobody can explain. The first call is with someone who can discuss the detail.