Onboard a new equipment package
Understand unfamiliar sensor fields, units, and timestamps, then organize the measurements around the equipment they describe.
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FactVerse Scout
Move equipment data into operations with less manual mapping
FactVerse Scout helps engineering teams discover equipment data, align it with assets and models, and publish reviewed connections through DFS Pro.
From unfamiliar fields to trusted operational context
Scout combines AI-assisted discovery with asset, model, and source context so engineering teams can prepare data connections with less manual investigation.
- Explore authorized data sources
Inspect available fields, schemas, units, timestamps, and sample values across approved live, file, and database sources.
- Add engineering context
Use device documents, templates, and model information to clarify what measurements represent and where they belong.
- Match equipment identities
Compare tags, serial numbers, locations, and existing master data to align records that refer to the same physical asset.
- Separate live and historical data
Identify the role of real-time feeds and historical files before selecting the right onboarding and analysis path.
- Review before publication
Keep proposed associations, supporting context, and open questions visible so responsible teams can confirm the result.
- Prepare data for operations and AI
Publish reviewed references for digital twins, monitoring, maintenance, analytics, and AI Agent workflows.
DFS Pro
Review the connection in one workspace
Scout brings discovered fields, equipment context, and proposed associations into a shared review surface. Teams can resolve ambiguity before the connection becomes part of an operational model.
- Compare source fields with equipment and measurement context
- Keep source references and unresolved questions visible
- Publish reviewed associations into the governed DFS workflow
Start with a practical data-onboarding challenge
Scout is most useful where engineering context is needed to turn fragmented source data into a reusable operational asset.
Unify records across systems
Reconcile equipment names and identifiers across monitoring, maintenance, spreadsheets, and master-data records.
Connect models and operational data
Use Brick-aligned model context to find relevant data, or use discovered measurements to improve model coverage.
Build data connections around engineering meaning
Equipment data often arrives with abbreviated field names, inconsistent units, different timestamps, and little explanation of how each value relates to the physical asset. Scout brings source metadata, sample values, equipment documents, and reusable templates into the same investigation so teams can understand the data before it enters an operational workflow.
Engineers can compare live feeds with historical files, identify useful measurements, and capture the questions that still need field knowledge. This shortens the path from first access to a connection plan that data owners and operations teams can review together.
Keep asset identity, measurements, and models aligned
The same pump may appear under a tag in the monitoring system, a serial number in a spreadsheet, and a different name in the maintenance platform. Scout works with FactVerse master data management to compare these records and prepare a consistent equipment view while preserving source lineage.
Brick-aligned model context adds the relationships between systems, equipment, and measurement points. Teams can use the model to find relevant data, then use discovered measurements to extend model coverage and strengthen the context available to digital twins and AI.
Turn each onboarding project into a reusable foundation
Reviewed associations become governed DFS references that can serve monitoring, maintenance, analytics, digital twins, and FactVerse AI Agent workflows. Starting with one equipment group gives the team a focused result to validate; approved patterns, mappings, and templates can then support the next source and the next site.
Frequently Asked Questions
Is Scout part of DFS Lite or DFS Pro?
Scout is a DFS Pro capability. An administrator enables access and assigns roles for exploration, review, and publication according to the project workflow.
What determines source and device coverage?
Coverage depends on the deployed connectors, authorized sources, supported formats, and available equipment information. DataMesh assesses additional protocols and formats as part of the integration scope.
Can we use Scout in a private environment?
Yes. Access to approved data sources and a reachable LLM service can be arranged according to the customer network, security, and deployment policy.
Related Content
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Guides
Bring your next data source into operational context
Start with one equipment scope and a result your engineering and operations teams can review together.