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Brando::Representing Brand-as-Code

Brand Oracle (Brando) Vocabulary v1.3

Brando® — the Brand Oracle — is an AI-native linked-data standard and Brand Definition Vocabulary (BDV).

It enables Brand-as-Code by tokenising brand intelligence — identity, expression, context, governance, and personas — as structured, machine-actionable semantics. These tokens form a Brand Knowledge Graph, from which Machine-Actionable Policy Graphs are derived and enforced by AI systems with precision.

Brando Schema: AI-native vocabulary for brands

Why Brando exists

Advanced Analytica is pioneering the use of JSON-LD (JavaScript Object Notation – Linked Data) as a control and governance layer for LLMs, agents, and generative AI systems.

Our research into foundation model training and inference shows that:

  • JSON-LD and Schema.org patterns are deeply embedded in model training data
  • graph-structured semantics are interpreted reliably by LLMs
  • linked data provides a stable, tool-independent way to encode intent, rules, and constraints

Brando — short for Brand Oracle — formally extends Schema.org beyond a purely descriptive SEO layer into an operative, governance-capable layer for AI-native systems.

Rather than replacing existing Schema Markup, Brando reuses and extends it, allowing organisations to:

  • minimise rework,
  • accelerate adoption,
  • and evolve static brand guidelines into Brand-as-Code.

Brand-as-Code and brand tokenisation

At the core of Brand-as-Code is brand tokenisation — the process of decomposing brand identity, expression, context, and governance into explicit, machine-readable brand tokens.

These tokens are not latent embeddings or informal prompts. They are first-class semantic units that can be:

  • referenced and versioned,
  • inherited and overridden,
  • governed by policy,
  • resolved dynamically at runtime.

Together, they form the nodes of a Brand Knowledge Graph, from which Machine-Actionable Policy Graphs are derived to constrain and guide AI behaviour.

→ Read: Brand tokenisation (Brand-as-Code)

Brando, IBOM, and the operating model

Brando is not just a vocabulary — it is the foundational data layer of the Brando Intelligent Brand Operating Model (IBOM).

  • Brando Schema defines what brand intelligence is and how it is tokenised.
  • Brando IBOM defines how that intelligence is assessed, codified, deployed, operated, and assured across AI systems and enterprise platforms.

Together, they allow brand to operate as governed infrastructure, not static documentation.

  • Brando IBOM → operating lifecycle and discipline
  • Brando → data model, vocabulary, executable semantics

→ Read: The Brando Intelligent Brand Operating Model (IBOM)

Brando as a “Brand Brain” (precisely defined)

Brando is often described as a “Brand Brain” — a useful metaphor when used carefully.

Like a brain, Brando:

  • stores structured memory (tokenised identity, values, and rules),
  • reasons across context,
  • governs behaviour,
  • guides action.

Unlike vague or metaphorical “brand brains”, Brando is:

  • explicitly structured, not latent,
  • auditable and versioned, not opaque,
  • policy-driven, not purely generative,
  • designed for enterprise governance and assurance.

Brando is not a model. It is the authoritative brand intelligence that models and agents must obey.

Brand Knowledge Graphs and Policy Graphs

Brando deliberately separates knowledge from execution.

Brand Knowledge Graph

The Brand Knowledge Graph represents:

  • tokenised brand identities and portfolios,
  • contexts, audiences, channels, and jurisdictions,
  • verbal, visual, and audio identity tokens,
  • personas, campaigns, and classifications,
  • governance metadata and constraints.

It answers:

“What brand intelligence exists?”

Machine-Actionable Policy Graphs

From the Knowledge Graph, Brando derives Machine-Actionable Policy Graphs that encode:

  • permissions and prohibitions,
  • enforcement levels,
  • refusal and escalation strategies,
  • risk, compliance, and regulatory logic,
  • temporal and contextual overrides.

They answer:

“What is allowed, required, or forbidden right now, in this context?”

At runtime:

Brand Knowledge Graph
└── Policy Graph (derived projection)
└── Executed by LLMs, agents, workflows

AI systems do not reason freely over the entire knowledge graph. They operate against policy-constrained projections.

What is Brando?

Brando is:

  • a linked data vocabulary and ontology extending Schema.org,
  • a Brand Definition Vocabulary (BDV) encoding intent, rules, and behaviour,
  • the authoritative Brand Knowledge Graph for Brand Operating Systems,
  • the source of executable Policy Graphs under IBOM.

Namespace: https://brandoschema.com/ Prefix: brando:

It:

  • extends schema:Brand and schema:Intangible,
  • aligns with GS1 Web Vocabulary, UNSPSC, and Google Product Taxonomy,
  • is published canonically in JSON-LD,
  • is profiled in YAML for operational use.

What this documentation covers

  • Getting started – motivation and adoption patterns
  • Quickstarts (JSON-LD / YAML)
  • Types and Properties references
  • Brand Operating System architecture
  • Brand tokenisation and runtime integration
  • Worked examples

Core concepts and classes

Brando v1.3 defines twelve core classes:

Class Purpose
brando:Brand Core brand identity
brando:Context Activation context
brando:BrandExpression Abstract expression superclass
Brando:VerbalIdentity Voice and language
Brando:VisualIdentity Visual system
Brando:AudioIdentity Sonic identity
brando:Policy Governance rules
brando:BrandedCategory Taxonomy alignment
brando:Campaign Temporal overrides
brando:AutomationRule Automated governance
brando:ProductPersona Product-scoped AI
brando:SyntheticPersona Governed AI persona

All classes extend schema:Intangible; brando:Brand extends schema:Brand.

Canonical form and profiles

Brando is JSON-LD–first.

Two profiles are provided:

  1. JSON-LD profile — publication and runtime
  2. YAML profile — configuration and CI/CD

A TypeScript model is provided as non-normative convenience.

Example: minimal brand (JSON-LD)

{
  "@context": {
    "schema": "https://schema.org/",
    "brando": "https://brandoschema.com/"
  },
  "@id": "https://example.com/brand/northstar",
  "@type": "brando:Brand",
  "schema:name": "Northstar Bank",
  "brando:missionStatement": "Financial clarity with absolute trust."
}

From vocabulary to running Brand OS

  1. Tokenise brand intelligence with Brando
  2. Build a Brand Knowledge Graph
  3. Derive Policy Graphs
  4. Execute at runtime
  5. Monitor and evolve under IBOM

Versioning and licensing

  • Vocabulary: Brando Schema v1.3
  • Ontology version: 1.4
  • Publisher: Advanced Analytica
  • License: CC BY 4.0

Stewardship

Brando is originated and stewarded by Advanced Analytica.

Implementation support

Advanced Analytica offers a Brando Implementation Service for full Brand OS delivery.

Next steps

  • Read Getting Started
  • Explore Brand tokenisation
  • Model your first brand
  • Plan Brand OS integration