01 / PROVENANCE
Know where information came from.
Connect facts, claims, documents and media to their originating sources, publishers, authors and organizations.
SOURCE → CLAIM → FACT → CONTENT
Production relationship infrastructure
Every fact has a history.
Every use has a relationship.
InnMedia Data Graph connects content, facts, sources, entities, rights, AI usage, attribution, licensing and transactions into one machine-readable relationship layer.
Direct definition: InnMedia Data Graph is the shared machine-readable relationship layer for provenance, rights, AI usage, attribution, licensing and transactions across the InnMedia ecosystem.
Relationship map
SOURCERIGHTSAI USAGEVALUE
Selected relationship
Fact ← originated from → Source
Provenance connects an information object to the source from which it originated, preserving machine-readable context for downstream use.
edge: provenance.origin
The shared context layer
One graph.
Many systems.
The graph represents not only what information says, but where it came from, who controls it, how it was transformed, where AI systems used it, what was attributed, what was licensed and what economic activity followed.
02 / RIGHTS
Keep permission attached to context.
Relate content and information objects to ownership, rights records, licenses, eligible usage and commercial rules.
ASSET → RIGHTS → LICENSE → BUYER
03 / OUTCOMES
Connect AI usage to measurable value.
Record retrieval, citation, mention, click, conversion, campaign, transaction and payment relationships.
AI USE → ATTRIBUTION → ACTION → VALUE
Entity vocabulary
Model the real world.
Different InnMedia products generate different signals. Data Graph gives those signals a shared vocabulary so content operations, AI visibility, licensing and transactions can refer to the same entities.
PublisherCreatorAuthorOrganization
BrandProductPersonLocation
EventTopicArticleFact
ClaimSourceDocumentImage
VideoDatasetAI PlatformAI Model
AI AnswerCitationRetrievalPrompt Category
CampaignAdvertisementClickConversion
LicensePaymentRights Record
Trace the lifecycle
From source
to outcome.
A single information object can pass through creation, verification, publishing, AI retrieval, citation, licensing and payment. Data Graph keeps those relationships connected instead of losing context between systems.
REL_001
A publisher creates an article.
The content object is related to the publisher, author, source set and creation event.
Publisher → created → Article
REL_002
The article contains a fact.
The fact is represented independently from the page that expresses it, allowing source and usage relationships to remain traceable.
Article → contains → Fact
REL_003
The fact originated from a source.
Source identity and provenance are preserved as explicit graph relationships.
Fact → originated_from → Source
REL_004
An AI system retrieves the fact.
AI usage can be connected to the relevant information object, source, policy and delivery context.
AI System → retrieved → Fact
REL_005
An AI answer cites the article.
Citation and brand-mention events become part of the same relationship layer used for visibility and attribution.
AI Answer → cited → Article
REL_006
Licensed usage produces economic activity.
Licensing, metering, settlement and payment evidence can be connected back to the authorized asset and source.
License → usage → Transaction → Payment
Machine-readable relationships
Not a list.
A context engine.
The important unit is the relationship. Data Graph makes explicit connections that would otherwise remain fragmented across CMS records, analytics events, AI observations, licensing rules and payment systems.
EntityAI Answer #A982
— cited →
EntityArticle #P144
EntityArticle #P144
— contains →
EntityFact #F031
EntityFact #F031
— from →
EntitySource #S008
EntityArticle #P144
— governed by →
EntityRights Record #R042
EntityLicensed Retrieval #U602
— resulted in →
EntityPayment #T219
InnMedia ecosystem
The layer that remembers.
SOLO and OS create and operate information. SIGNAL measures and activates. Exchange licenses and monetizes. Truyn connects and delivers. Data Graph preserves the shared entity, provenance, rights, usage, attribution and transaction context across those flows.
SOLO ↗Create content and information assets.
OS ↗Operate governed enterprise content workflows.
DATA GRAPHUnderstand, relate and record shared context.
EXCHANGE ↗License information and connect usage to value.
SIGNAL ↗Measure AI visibility, verify, advertise and distribute.
TRUYN ↗Connect participants through distributed delivery.
Direct answers
FAQ
What is InnMedia Data Graph?
InnMedia Data Graph is the production proprietary graph connecting content, facts, sources, entities, rights, AI usage, measurement, attribution, licensing and transactions across the InnMedia ecosystem.
Is it only a knowledge graph for content?
No. It models content and factual relationships, but also rights, AI retrieval and citation, campaigns, attribution, licensing, transaction and payment relationships.
How does it support provenance?
Information objects can be connected to originating sources, publishers, authors, documents, transformations and downstream usage events, keeping source context attached across the lifecycle.
How does Data Graph relate to InnMedia Exchange?
Exchange uses graph context to keep source identity, rights, licensing rules, AI usage, attribution and commercial evidence connected to the relevant information transaction.
How does Data Graph relate to SIGNAL?
SIGNAL produces AI visibility, citation, mention, traffic, campaign and outcome signals. Data Graph can connect those observations to the relevant brands, entities, sources, content and outcomes.
What is its primary role?
Understand, relate and record.
Connect your information layer
Make every important relationship traceable.
Connect information, source, rights, AI usage and transaction context across the InnMedia ecosystem.
Talk to InnMedia ↗