Skip to content
AI-NATIVE SCADA & DIGITAL TWIN

Nothing reaches the plantuntil it has been proven.

Djinious supervises your plant in real time, turns an operator's intent into a runnable procedure, proves that procedure on an isolated twin, and only then asks a human to approve it. The loop is closed, and every step of it is auditable.

  1. Observe
  2. Author
  3. Prove
  4. Act
The Djinious copilot showing a proposed high-wind curtailment procedure, its dry-run on an isolated twin with all four assertions passing, six intercepted field commands, and an approve-and-execute gate labelled C4 operational action.
The copilot's proposal, dry-run on an isolated twin: assertions held, six field commands intercepted, and a C4 approval gate before anything is issued.Djinious copilot · Provence Hybrid Plant
4
plants running
energy, water, gas, discrete
392
live tags
54 writable · 129 alarmable
3
field protocols
OPC-UA · Modbus · Sparkplug
C0–C6
authority classes
L0–L4 autonomy
THE LOOP

Four stages, and a gate between intent and the field

This is the whole product. Everything else — the historian, the alarm engine, the drivers, the twin — exists to make one of these four stages true.

  1. 01

    The plant, and its twin, in one place

    Real-time supervision on ISA-101 high-performance screens, backed by a continuously synced digital twin. Neutral grey is the resting state; colour means something is wrong.

    • 1 Hz acquisition over OPC-UA, Modbus TCP and MQTT Sparkplug B — real drivers, not adapters-in-name
    • Every tag historised to TimescaleDB and queryable back through the same API
    • ISA-18.2 alarm management: priority, shelving, out-of-service, second-person acknowledgement
    • Mimics you draw in the Builder are the same graphics the Runner shows — no parallel drawing set
  2. 02

    Intent becomes a procedure you can read

    An operator states what they want. The copilot grounds it in the live twin and emits a Process Intent Representation, which compiles to executable BPMN and is statically validated before anyone sees it.

    • Grounding first: the copilot resolves the intent against real assets, tags and limits
    • PIR → BPMN with a validation report — required capabilities, authority class, blast radius
    • Human-readable procedure: capability steps, decisions, human tasks, notifications
    • Deterministic. The closed loop needs no external LLM; one can be attached, never depended on
  3. 03

    Run it against a twin that cannot touch the field

    The procedure is dry-run on an isolated simulation twin with a virtual clock and a seeded RNG. Field commands are intercepted. Assertions are evaluated against what the twin actually measured.

    • Structurally isolated: every command the procedure issues is caught before a connector sees it
    • Reproducible: same seed, same trajectory, bit-exact on replay
    • Run the scenario without the procedure first — the baseline must fail for the proof to mean anything
    • Both the scenario's assertions and the procedure's own acceptance criteria are checked
  4. 04

    Execution a regulator could follow

    Approval issues real commands through interlocks, policy and read-back. Authority classes bound what an agent may ever request; autonomy levels bound whether it may execute at all.

    • Authority C0–C6 and autonomy L0–L4, granted per agent, per scope, with an expiry
    • Interlocks evaluated before every write; a failed check is an incident, not a retry
    • Read-back from an independent applied-setpoint echo — never the register just written
    • Kill switch, second-person approval, and a timestamped, attributed audit trail
THE PROOF STEP

A dry-run only counts if the baseline fails

Every procedure below ships with the scenario that proves it. The same scenario is run twice — once without the procedure, once with it. If the baseline passes, the procedure has proven nothing, and Djinious shows you that.

Dry-run results for each plant: the measured baseline, the measured result with the procedure, and the limit each is checked against.
PlantScenarioMeasuredBaselineWith procedure
AQUAUF-03 fouling excursionTransmembrane pressurelimit 1.35 bar1.62 bar — fail0.56 bar — pass
CAMGCMP-01 suction restrictionAnti-surge marginlimit 12 %−32.3 % — fail+16.6 % — pass
BLN3Filler overspeed pushReject ratelimit 3.5 %9.40 % — fail1.90 % — pass
PROVHigh-wind gust frontWind-field powerlimit 1.3 MW3.60 MW — fail1.08 MW — pass

Read off the isolated simulation twin. Baseline and mitigated runs use the same scenario, the same seed and the same virtual clock.

WHAT WE WILL NOT DO

This is control software. It does not pretend.

Djinious runs against real plant. So the product refuses to fake: a tag in LIVE mode takes its value from a device read or reports no data; simulation is labelled SIM wherever it appears; an unimplemented capability is shown as unimplemented rather than mocked; and a lost connection turns a lamp grey, never green.

  • A LIVE tag with no fresh device read reports not-connected — it never falls back to the model
  • Command read-back reads an independent echo, so an acknowledgement cannot be tautological
  • The simulation twin is labelled, isolated, and its intercepted commands are listed
  • Where a protocol adapter is a stand-in, the connectivity page says so on the card

Bring us your plant.

We will stand Djinious up against your tags, your alarm philosophy and one procedure you actually run — and dry-run it in front of you.

DjiniousControl Center

Supervise the plant, author the procedure, prove it on an isolated twin, execute under policy. One governed loop.

  1. Observe
  2. Author
  3. Prove
  4. Act

Every screenshot on this site is a capture of the running platform.