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The Operational State Monitoring (OSM) agent continuously labels which operating regime a system is in, from a small set of N-shot labeled examples gathered across environments or sessions. There is no concept of normal or anomalous; every regime is a valid state, and the agent simply reports which one the system currently occupies. Unlabeled data can be incorporated to improve coverage.

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Use Cases

  • Monitor asset condition and performance: Classifies every window into an operating state, turning the raw sensor stream into a continuous, timestamped state record.
  • Detect process drift and degradation: Tracks each state’s dwell time over rolling periods, so slow decline shows up early.
  • Identify and maintain optimal operating envelopes: Reveals the operating envelope as the states an asset normally holds, so out-of-range behavior stands out.

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See an Interactive Example

Try out the OSM agent with predefined data sets using our interactive examples. We have two examples available:

OSM Drill Agent

Classifies the operational state of a drilling rig. Reads nine sensor channels from a North Sea well and labels each time window as one of six states: drilling, reaming, off bottom, in slips, trip in slips, or shut in.

OSM HVAC Agent

Classifies the operating state of a fan coil unit. Reads six sensor channels and classifies them as a stuck valve, a stuck damper, or a heating-side fault.

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Using the Archetype AI Python Client

How to use the Archetype AI Python client to work with the OSM agent.

Operational State Monitor Agent Example

An example that runs an Operational State Monitor (OSM) agent on sensor data using a platform-hosted quick-start bundle.