Asset Graph and Context Lake

Give every signal
the context that makes it meaningful.

The Asset Graph & Context Lake is Lumicent's multimodal data foundation. It creates a structured representation of the physical operation and connects every incoming signal to the asset, location, operating role and business context it belongs to.

The foundation combines:

  • Asset hierarchy — site → line → asset
  • Time-series physical telemetry
  • Asset metadata and criticality
  • Business Impact Assessments
  • Maintenance and operational history
  • Labeled faults, interventions and near misses
  • ERP, EAM and other enterprise context where available

Under the hood, time-series, relational and vector data infrastructure work together to support telemetry, asset records, machine-learning embeddings and similarity analysis.

What it does

The Asset Graph stores, validates and structures the information needed by every intelligence layer above it.

Incoming physical data is authenticated and associated with a known asset. That telemetry becomes part of a continuously growing history of how the asset behaves, what has happened to it, what interventions have occurred and what the asset means to the surrounding operation.

The platform can also ingest context such as replacement cost, maintenance history, production role and asset master information from ERP and EAM systems where available.

How it's better

Most industrial data is fragmented.

Telemetry sits in one system. Asset metadata sits in another. Maintenance history sits in EAM. Business-criticality information may live in spreadsheets or in people's heads.

Lumicent creates a connected model in which physical data and operational context can be evaluated together.

And unlike architectures that require extensive enterprise integration before they create value, Lumicent can establish this foundation from its own sensing infrastructure first. External systems enrich the model but are not prerequisites.

The accumulated operational history also creates a compounding advantage: faults, interventions and other labeled events provide additional context for models and analysis over time.

Business value

The Asset Graph turns disconnected readings into a living representation of asset health and operational relevance.

That provides the context required to move beyond “this sensor changed” to “this specific asset changed, this is how it has behaved historically, this is what depends on it, and this is why the change matters.”

What you get: an asset-aware data foundation that makes every layer of intelligence above it more precise and useful.

Act before exposure
becomes loss

See how Lumicent helps physical operations teams reveal emerging risk, prioritize what matters most, and drive action before failure occurs.

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Frequently asked questions

What is the Lumicent platform?

Lumicent is a Decision Intelligence platform for physical operations. It continuously captures physical asset conditions, identifies meaningful changes, connects them with asset and business context, evaluates potential consequence and ranks emerging risks according to what deserves attention first.

How does the Lumicent platform work?

Lumicent moves from physical signal to prioritized action. Edge sensing captures asset-condition data. The Asset Graph adds physical and operational context. Signal Intelligence identifies meaningful change. Consequence Intelligence evaluates what that change could mean. Decision Intelligence ranks what matters most. The Decision Center then explains and delivers those priorities to the people responsible for acting on them.

How is Lumicent different from condition monitoring?

Condition monitoring primarily identifies abnormal asset conditions. Lumicent goes further by determining the potential consequence associated with those conditions and comparing them against other emerging risks. The goal is not simply to identify more problems. It is to determine which problems matter most.

What is Signal Intelligence?

Signal Intelligence is Lumicent's statistical and machine-learning analysis layer. It evaluates physical asset behavior over time to identify anomalies, trends, drift, acceleration and other meaningful changes that may indicate a developing condition.

What is Consequence Intelligence?

Consequence Intelligence connects a changing physical condition with the potential Operational, Safety, Financial, Compliance, Environmental and Reputational impact associated with that specific asset.

What is Decision Intelligence?

Decision Intelligence combines physical-condition intelligence with consequence to create a continuously updated, ranked view of what deserves attention most, why and where intervention can have the greatest impact.

Does Lumicent require integration with SCADA, ERP or EAM?

No. Lumicent can operate using its own sensing and intelligence infrastructure. SCADA, ERP, EAM, CMMS and other systems can provide additional context or receive Lumicent intelligence where useful, but those integrations are additive rather than prerequisites.

Is Lumicent a hardware or sensor platform?

No. Lumicent is software-first. Sensors and edge infrastructure provide the continuous physical evidence the platform needs, but the differentiated value comes from what the software does with that evidence: understand changing conditions, determine consequence and prioritize action.

How does Lumicent use AI and machine learning?

Lumicent uses statistical analysis, machine learning and Physical AI to interpret real-world asset behavior, identify meaningful patterns, support dynamic risk scoring, prioritize emerging risk and translate complex analysis into usable intelligence. AI is an enabling mechanism rather than the end product. Its purpose is to extend human judgment and help people make earlier, better-prioritized decisions in environments where the consequences are physical and real.