Master Comparison Matrix & Overlap Heatmap

Section C — Areas of technical correspondence

Master comparison matrix

Each cell records the strength of correspondence between a capability of the proposed patent architecture and the reviewed public material of each company. Select any cell to open the supporting public evidence and the analysis behind the rating. No cell asserts infringement; ratings describe publicly demonstrated capability only.

Strong public correspondence

Moderate public correspondence

Partial correspondence

Not identified in reviewed public material

Different implementation / objective

Capability / Patent Pillar	Proposed Patent Architecture	Adobe	Microsoft	Meta	Google	AWS	Salesforce	NVIDIA
AI orchestration	Central orchestration layer coordinating agents, twins, memory and external platforms on behalf of a named principal.
Creator AI Agent	Agent bound to a creator principal, executing publication, audience and commercial workflows across independent platforms.
Viewer AI Agent	Agent acting for the viewer, filtering and proactively retrieving content across the platforms the viewer uses.
Specialised agents	Defined family of functional agents (publication, rights, sponsorship, analytics) with declared authority and interaction semantics.
Agent-to-agent communication	Inter-agent discovery, delegation and preliminary commercial negotiation between agents bound to opposing principals.
Digital Twins	Persistent principal-owned model of a creator, viewer or content item, queryable by agents and portable across platforms.
Behavioural Digital Twins	Behavioural state derived from observed cross-platform activity and revised against measured outcomes.
Digital Content Twins	Persistent identity for a work, tracking derivatives across modality changes and independent platforms.
Persistent memory	Long-horizon memory generated from executed actions and their results, not from dialogue alone.
Knowledge graphs	Semantic graph relating creators, audiences, works, rights and commercial agreements.
Predictive intelligence	Prediction of audience response, content performance and commercial outcome conditioned on twin state.
Content lifecycle	Agent-driven orchestration from ideation through transformation, publication, measurement and re-optimisation.
AI content transformation	Automated derivation of platform-specific variants governed by twin state and rights constraints.
Multimodal semantic search	Retrieval across text, image, audio and video conditioned on the requesting principal's behavioural state.
Cross-platform audience intelligence	Audience overlap, migration and value analysis aggregated across platforms the operator does not control.
Commercial orchestration	Agent-mediated valuation, offer handling and performance-linked settlement of commercial arrangements.
Sponsorship orchestration	Bilateral negotiation between creator and sponsor agents with entitlement checks and outcome verification.
Rights management	Rights state held against the content twin and acted upon autonomously across independent platforms.
Provenance	Lineage record linking a work to its derivatives with confidence scoring, consumable by agents.
Authenticity	Verification of authorship and AI involvement as an input to rights and commercial decisioning.
Intelligent notifications	Attention management in which the agent suppresses, aggregates or escalates based on predicted principal value.
Enterprise / API orchestration	Connector layer permitting agents to act on external systems under delegated, revocable authority.
Distributed AI	Distribution of inference and model state across edge and cloud components of the architecture.
Privacy-preserving AI	Behavioural state usable for prediction without exposing raw cross-platform activity to counterparties.
Explainable AI	Explanation of agent decisions and recommendations by reference to twin state and observed outcomes.
Continual learning	Ongoing revision of principal-specific models from measured results rather than population-level training.
Autonomous workflow execution	Execution of multi-step workflows on external platforms without step-by-step human instruction.
Feedback-based optimisation	Closed loop in which measured commercial and audience outcomes write back to the twin and condition later strategy.

“Not identified in reviewed public material” records the limits of this review only. It is not a statement that a company lacks the capability; internal or unpublished systems cannot be assessed from public sources.

Overlap heatmap

Correspondence density across pillars and companies

The same data rendered without labels so that concentration and gaps are immediately visible. Select any cell for the underlying evidence.

Strong public correspondence

Moderate public correspondence

Partial correspondence

Not identified in reviewed public material

Different implementation / objective

Capability / Patent Pillar	Proposed Patent Architecture	Adobe	Microsoft	Meta	Google	AWS	Salesforce	NVIDIA
AI orchestration	Central orchestration layer coordinating agents, twins, memory and external platforms on behalf of a named principal.
Creator AI Agent	Agent bound to a creator principal, executing publication, audience and commercial workflows across independent platforms.
Viewer AI Agent	Agent acting for the viewer, filtering and proactively retrieving content across the platforms the viewer uses.
Specialised agents	Defined family of functional agents (publication, rights, sponsorship, analytics) with declared authority and interaction semantics.
Agent-to-agent communication	Inter-agent discovery, delegation and preliminary commercial negotiation between agents bound to opposing principals.
Digital Twins	Persistent principal-owned model of a creator, viewer or content item, queryable by agents and portable across platforms.
Behavioural Digital Twins	Behavioural state derived from observed cross-platform activity and revised against measured outcomes.
Digital Content Twins	Persistent identity for a work, tracking derivatives across modality changes and independent platforms.
Persistent memory	Long-horizon memory generated from executed actions and their results, not from dialogue alone.
Knowledge graphs	Semantic graph relating creators, audiences, works, rights and commercial agreements.
Predictive intelligence	Prediction of audience response, content performance and commercial outcome conditioned on twin state.
Content lifecycle	Agent-driven orchestration from ideation through transformation, publication, measurement and re-optimisation.
AI content transformation	Automated derivation of platform-specific variants governed by twin state and rights constraints.
Multimodal semantic search	Retrieval across text, image, audio and video conditioned on the requesting principal's behavioural state.
Cross-platform audience intelligence	Audience overlap, migration and value analysis aggregated across platforms the operator does not control.
Commercial orchestration	Agent-mediated valuation, offer handling and performance-linked settlement of commercial arrangements.
Sponsorship orchestration	Bilateral negotiation between creator and sponsor agents with entitlement checks and outcome verification.
Rights management	Rights state held against the content twin and acted upon autonomously across independent platforms.
Provenance	Lineage record linking a work to its derivatives with confidence scoring, consumable by agents.
Authenticity	Verification of authorship and AI involvement as an input to rights and commercial decisioning.
Intelligent notifications	Attention management in which the agent suppresses, aggregates or escalates based on predicted principal value.
Enterprise / API orchestration	Connector layer permitting agents to act on external systems under delegated, revocable authority.
Distributed AI	Distribution of inference and model state across edge and cloud components of the architecture.
Privacy-preserving AI	Behavioural state usable for prediction without exposing raw cross-platform activity to counterparties.
Explainable AI	Explanation of agent decisions and recommendations by reference to twin state and observed outcomes.
Continual learning	Ongoing revision of principal-specific models from measured results rather than population-level training.
Autonomous workflow execution	Execution of multi-step workflows on external platforms without step-by-step human instruction.
Feedback-based optimisation	Closed loop in which measured commercial and audience outcomes write back to the twin and condition later strategy.

Strategic correspondence score

Weighted methodology and underlying scoring table

Category scores express how strongly each company's reviewed public material corresponds with that part of the proposed architecture. The weighted total is calculated from the published weights; no score has been adjusted to produce a particular ranking.

Category (weight)	Google	Salesforce	Adobe	Microsoft	Meta	AWS	NVIDIA
Core architectural correspondence (30%)	84	84	88	90	62	80	58
AI Agent correspondence (15%)	90	90	78	92	74	85	66
Digital Twin / behavioural modelling (10%)	50	62	55	40	68	30	58
Memory / knowledge architecture (10%)	88	84	70	92	72	90	46
Creator / content / audience correspondence (15%)	80	52	72	45	94	20	18
Enterprise / API orchestration (10%)	88	94	90	95	40	92	72
Commercial / rights / provenance correspondence (5%)	78	84	82	55	66	40	22
Continual learning / predictive intelligence (5%)	76	78	74	70	90	62	62
Weighted total / 100	81.0	78.6	78.2	76.5	69.6	66.1	51.8
Preliminary hypothesis (tested, not adopted)	96	95	99	98	97	94	90

Google

81.0

Google records high agent and memory correspondence, and unusually high creator correspondence because of YouTube. Digital Twin correspondence is scored low: reviewed public material does not identify behavioural twin constructs. Core correspondence is reduced because agent infrastructure and creator ecosystem are documented as separate offerings.

Salesforce

78.6

Salesforce records strong orchestration, agent, memory and commercial correspondence. Creator/content/audience correspondence is limited: creator-ecosystem and content-rights functions are not identified in reviewed public material.

Adobe

78.2

Adobe scores highest on core architectural correspondence because the publicly described content supply chain is the nearest documented analogue to the proposed lifecycle-plus-feedback loop, and highest on commercial/rights/provenance because of Content Credentials. Digital Twin correspondence is scored low: reviewed public material describes customer profiles and segments, not behavioural twins acting for the modelled party.

Microsoft

76.5

Microsoft records the strongest agent, memory and enterprise correspondence of any company reviewed. Creator/content/audience correspondence is scored low because creator-ecosystem and audience-intelligence functions are not identified in reviewed public material for this platform.

Amazon Web Services

66.1

AWS records strong infrastructure correspondence and the lowest creator/content/audience correspondence of the seven, reflecting its platform orientation. The resulting score is below the preliminary hypothesis and the ranking has been adjusted accordingly.

NVIDIA

51.8

NVIDIA's twin score reflects strong technical twin capability in a different domain, scored for architectural rather than domain correspondence. Creator and commercial correspondence are the lowest of the seven. The resulting score sits materially below the preliminary hypothesis.

Departure from the preliminary hypothesis. The hypothesis placed all seven companies between 90 and 99. The evidence-derived weighting produces a wider distribution. Adobe remains highest on core architectural correspondence; Microsoft, Google and Salesforce cluster closely behind on agent, memory and enterprise correspondence; Meta records the highest creator-domain correspondence but materially lower core orchestration correspondence; AWS and NVIDIA fall well below their hypothesised positions because creator, audience, sponsorship and rights functions are not identified in reviewed public material for those platforms.

Marked: Patent Position Analysis / Technical Interpretation. Scores are an analytical instrument for prioritising further technical and legal review, not a legal conclusion.