Product · Ontology
Your vocabulary, as objects and links.
The ontology turns raw tables into business objects (an asset, an engagement, a supplier, a site) linked together, which teams and agents act on directly.
Not a blank page
General-purpose platforms can build ontologies, but rarely ship a ready-to-use domain model: it is up to the client to build it. An expert firm has neither the budget nor the team to model its business from scratch.
ArborSpace ships with a first model of the domain (energy assets, due diligence engagements) that the firm adapts rather than builds.
What the firm declares
- Asset classes, such as a class 7F gas turbine.
- Engagements, such as a technical due diligence.
- Stakeholders, such as the lender financing an asset.
- Relationships between them: installed at, assessed in, delivered to.
Example
One reading, five connected objects.
A vibration above 8.2 mm/s on a class 7F gas turbine generates a finding. That finding is linked to the asset, the site, the engagement and the lender concerned, along with the rule that produced it.
rule VIB-002 (version 3)
if asset.class = GAS-TURBINE-7F
and bearing_vibration > 8.2 mm/s
then finding "Vibration above threshold"
reviewed by a senior engineer- FindingVibration above 8.2 mm/sconcerns
- AssetClass 7F gas turbineinstalled at
- SiteCombined-cycle power plantassessed in
- EngagementTechnical due diligencedelivered to
- LenderThe bank financing the asset
The pilot
Six weeks on a narrow scope of your firm.
The question to answer at the end is simple: is the captured memory worth extending to the rest of the firm?
- Weeks 1–2Write the first fifteen rules, starting from three questions put to your experts.
- Weeks 3–6Apply them to your own engagements.