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Platform · Ontology ]

The business context layer behind every answer

Pluvo's ontology models how your business actually works: the entities, relationships, and definitions behind your numbers, so agents reason over your company instead of guessing at it.

Entities · Relationships · Definitions

Knowledge graphSearch nodes...
440 nodes · 584 edges

Meaning, modeled once. Define what revenue means, how entities relate, and which rules apply, then every question, workflow, and report computes from the same understanding.

A living map of your business

Customers, contracts, products, entities: the ontology captures what exists and how it all connects, across every system you run.

  • Entities resolved across systems

    One customer, one record, whether it lives in your CRM, billing, or ERP.

  • Relationships made explicit

    A contract governs a purchase; revenue flows from it. The map holds the how.

  • Independent of your tools

    The model reflects your business, not any one system's schema.

BUSINESS CONTEXT
CustomersignsContractgeneratesRevenue
Revenue = recognized · fiscal calendar · all four entities

Definitions that end the debate

Every company defines revenue differently. The ontology pins your definitions down so every answer, human or agent, uses the same ones.

  • One definition, everywhere

    Recognized vs booked, fiscal vs calendar: decided once, applied always.

  • Versioned and governed

    Definitions change; the history and the approvals stay.

  • Consistent outputs

    Two people asking the same question get the same number.

OPEX · JUNE · ALL ENTITIES · USD
$1,284,410
NetSuite · GL 6000–6999$1,201,330
Ramp · card spend$71,080
FX adjustment · CAD→USD$12,000
SAME INPUTS → SAME ANSWER

Built for agents to reason over

AI is only as good as the context you feed it. The ontology is the stable, machine-readable context that lets agents understand instead of guess.

  • Context without the scavenger hunt

    Agents traverse the map instead of stitching exports together.

  • Grounded computation

    Answers computed against your logic, not a generic model's assumptions.

  • A compounding asset

    Every definition and relationship you add makes every future answer better.

CONNECTED SYSTEMS
NetSuiteGL · read-onlySynced 2m ago
RampSpend · read-onlySynced 4m ago
RipplingHR · read-onlySynced 11m ago
StripeBilling · read-onlySynced 1m ago

What one shared model changes ]

3

building blocks: entities, relationships, definitions

1

shared model every system and agent reads from

0

conflicting definitions of a metric

Everyone finally argues about the business, not about whose number is right.

VP Finance · Multi-entity SaaS

Use cases ]

How finance teams use the Ontology

The context layer under every workflow, answer, and report.

  • Metric standardization

    One definition of ARR, margin, and burn across the company.

  • Entity resolution

    The same customer recognized across CRM, billing, and GL.

  • Multi-entity onboarding

    New entities mapped into the model, not bolted on.

  • Policy grounding

    Recognition and allocation rules applied automatically.

  • Agent context

    Every agent run starts from the same worldview.

Definition rolloutDone
Update revenue definitionv14
Recompute affected metrics38 metrics
Flag downstream reports6 flagged
Notify ownersSent

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FAQ ]

Common questions

What is a business ontology?
A business ontology is a structured model of what exists in your business (customers, contracts, products, entities), how those things relate, and what your terms mean. In Pluvo it is the context layer every answer, workflow, and report computes against.
How is an ontology different from a data model or schema?
A schema describes how one system stores data. The ontology describes how your business works independent of any system: the meaning of the objects and the relationships between them, consistent even when tools change.
Do we have to build the ontology ourselves?
No. Pluvo constructs it from your connected systems and your existing definitions; your team reviews and refines it rather than starting from a blank page.
What happens when a definition changes?
Definitions are versioned. When one changes, affected metrics recompute, downstream reports are flagged, and the history of what was defined when is preserved.
Why do AI agents need an ontology?
Agents fail on context, not intelligence. With an ontology, the relationships are already mapped and the meaning already defined, so an agent can reason over a model of your business instead of guessing from fragments.

See your business, modeled

Book a demo and watch Pluvo assemble the context layer from your own systems.