Industrial intelligence, contextualized

Prophet maps every system in your plant into one live model, so that AI can analyze what’s actually happening without guesswork.

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Prophet
Why did Line 3 stop at 2:14 pm?
  • Traced 14 upstream assets
  • Pulled 6 historian trends
  • Read the filler and capper interlocks
Prophet

Root cause: pasteurizer PST-201

Its heat exchanger faulted at 1:29. The surge tank covered for 45 minutes, then the capper starved. The capper isn't broken.

PST-201Outlet temp
T-210Surge tank level
FIL-301Line rate
Fault 1:29 Stop 2:14 ~45 min in the surge tank
1:001:302:002:30
PST-201.OutletTempT-210.LevelCAP-401.Starved
Help me make sense of my current alarms.
  • Pulled 32 active alarms from SCADA
  • Grouped them by cause
  • Ranked them by process impact
Prophet

32 alarms, 3 events. One needs action now.

A cooling water pump tripped. Reactor R-3 has about 20 minutes before its high-high limit.

  • TI-310Reactor R-3 temperature high
  • P-204Pump trip
  • FT-118Flow deviation
  • PT-311Jacket pressure low
  • FT-118Flow deviation
  • L2-CHGChangeover in progress
  • FT-118Flow deviation
  • + 25 more
  • 17
    Cooling water pump P-204 trippedAct now: start standby pump P-205.
  • 9
    FT-118 chatteringNo process impact. Schedule recalibration.
  • 6
    Line 2 changeoverExpected. Suppress during changeovers.
P-204.RunTI-310.PVFT-118.PV
How do I raise yield on Line 2?
  • Traced rejects back to their stations
  • Pulled 30 days of scrap and rework
  • Sized each fix against the target
Prophet

Three fixes, about +3.3 points of yield

Most of the loss is fill-level drift and out-of-spec capping, not line speed.

  • Correct fill-level driftFIL-301 underfills after long runs.
    +1.5
  • Recalibrate capper torqueCAP-401 torque drifts out of spec.
    +1.0
  • Cut changeover scrapFirst 20 minutes after each changeover.
    +0.8
Combined
Target +3 pts
+3.3
FIL-301.FillLevelCAP-401.TorqueL2.Changeover
  • Root cause in minutes
  • First-line operator support
  • Proactive fault detection
  • Alarm management
  • Yield optimization
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The problem

Context is the bottleneck. Plants already collect telemetry data. AI models can reason. What’s missing is what’s in between. Without a unified plant model, AI gives you guesses, not answers. That won’t cut it.

Introducing Prophet

The solution

A dynamic, deterministic context layer

01

Build context in minutes

Ingest controller backups, SCADA exports, databases, manuals, maintenance logs, even photos of the shift board. Prophet parses the OT artifacts deterministically, analyzes the rest with AI, and links it all into one unified plant model.

02

Deterministic mapping, down to the tag

Parsed, not guessed.

The model maps your process down to the individual PLC routines and tags. Every link traces back to the live control system code that creates it.

03

The context stays current

The PLC changed. Prophet noticed.

When a SCADA system or PLC program changes, Prophet ingests the new version and updates the model automatically, keeping the AI reliable and up to date.

04

It gets better with time

When your team corrects or teaches it, Prophet saves its learnings as persistent memory, creating new nodes and connections as needed.

05

Every answer traces back to the plant

The capper isn’t broken.

Ask a question and Prophet traces through the model, giving answers with direct tag-level citations. Everything is auditable.

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