Research works

Stater Currency Architecture

Governed purchase of heterogeneous AI capacity creates an accounting problem that is easy to misname and therefore easy to mis-build. When an organization reserves bounded budgets against nonfungible capacity offers, commits value to execution it does not control, and must later...

PRETIUM Market Reference Architecture

This paper proposes a reference architecture for PRETIUM, the internal economics component of the SkipJack Cognitive Exchange suite. The central proposal is deliberately minimal: a non-monetary, non-custodial internal accounting architecture may make heterogeneous AI-capacity eco...

The SkipJack Cognitive Exchange Suite: Six Bounded Contracts for Accountable Consumption of Heterogeneous AI Capacity

Organizations that consume artificial-intelligence capacity increasingly face a supply landscape that is materially heterogeneous: model APIs, tool services, retrieval endpoints, rented accelerators, and private inference profiles are metered, priced, capability-bounded, and cont...

Authority Before Optimization: Governing AI Capacity Selection

Organizations that buy artificial-intelligence capacity increasingly choose among heterogeneous routes to the same outcome: hosted model interfaces, private inference, rented accelerator time, tool and retrieval services, and local execution. The machinery that compares those rou...

NIMBUS Connect: Governed Execution Across Heterogeneous AI Capacity

Organizations that purchase artificial-intelligence capacity increasingly face a boundary problem: an authority layer may decide what work is eligible and issue a bounded grant, and an economic layer may commit a bounded budget against that grant, but the work must still be execu...

The AI Capacity Provider Standard

Organizations that consume AI capacity from more than one source face an immediate and largely unexamined measurement problem: the units in which that capacity is metered — tokens, requests, GPU-hours, invocations, retrieval calls — are defined by their issuers, priced by their i...

Verified Synthesis: From Agent Fan-Out to One Accountable Result

Organizations that dispatch one bounded request to several AI capacity providers receive back a set of outputs that partially agree, materially conflict, omit different evidence, and sometimes fail outright. This paper examines why possession of that fan-out set is not the same t...

Verified Synthesis: From Agent Fan-Out to One Accountable Result

Organizations that dispatch one bounded request to several AI capacity providers receive back a set of outputs that partially agree, materially conflict, omit different evidence, and sometimes fail outright. This paper examines why possession of that fan-out set is not the same t...

ARBITER Policy Reference Architecture

This paper proposes a reference architecture for ARBITER, the workload-authority and policy-routing member of the SkipJack Cognitive Exchange. It addresses one bounded question: what minimum functional stack could determine authority before optimization, issue a bounded route gra...

ARBITER Policy Reference Architecture

This paper proposes a reference architecture for ARBITER, the workload-authority and policy-routing member of the SkipJack Cognitive Exchange. It addresses one bounded question: what minimum functional stack could determine authority before optimization, issue a bounded route gra...

PRETIUM Market: The Economics of Cognitive Capacity

Organizations that buy AI capacity now purchase across model APIs, hosted inference, rented and preemptible GPU capacity, tool and retrieval services, and private local execution — capacity classes whose native meters do not share a unit, whose prices do not encode eligibility, a...

NIMBUS Connect: Governed Execution Across Heterogeneous AI Capacity

Organizations that purchase artificial-intelligence capacity increasingly face a boundary problem: an authority layer may decide what work is eligible and issue a bounded grant, and an economic layer may commit a bounded budget against that grant, but the work must still be execu...

NIMBUS Connect Reference Architecture

Heterogeneous artificial-intelligence work can cross local accelerators, remote model interfaces, private inference services, tools, protocol servers, rented capacity, and dedicated systems without becoming one homogeneous resource. That diversity creates a recurring architectura...

Stater Currency Architecture

Governed purchase of heterogeneous AI capacity creates an accounting problem that is easy to misname and therefore easy to mis-build. When an organization reserves bounded budgets against nonfungible capacity offers, commits value to execution it does not control, and must later...

Authority Before Optimization: Governing AI Capacity Selection

Organizations that buy artificial-intelligence capacity increasingly choose among heterogeneous routes to the same outcome: hosted model interfaces, private inference, rented accelerator time, tool and retrieval services, and local execution. The machinery that compares those rou...

The SkipJack Cognitive Exchange Suite: Six Bounded Contracts for Accountable Consumption of Heterogeneous AI Capacity

Organizations that consume artificial-intelligence capacity increasingly face a supply landscape that is materially heterogeneous: model APIs, tool services, retrieval endpoints, rented accelerators, and private inference profiles are metered, priced, capability-bounded, and cont...

From ISO/IEC 42001 to the EU AI Act: Mapping the Residual Compliance Work

Mapping residual EU AI Act compliance work after leading AI governance frameworks. Compares a multi-ISO stack (ISO/IEC 42001 and companions, including ISO 37301), IAPP AIGP and CIPP/E, and the NIST AI RMF (with generative-AI profile). By article-normalized weight, about 58% of th...

From ISO/IEC 42001 to the EU AI Act: Mapping the Residual Compliance Work

Mapping residual EU AI Act compliance work after leading AI governance frameworks. Compares a multi-ISO stack (ISO/IEC 42001 and companions, including ISO 37301), IAPP AIGP and CIPP/E, and the NIST AI RMF (with generative-AI profile). By article-normalized weight, about 58% of th...

Preparation-Dependent Structure and Selective Hydrogenation Performance of Pt Nanoparticles Supported on Low-Dimensional Carbon Materials

This preprint investigates the influence of preparation methodology on the structure, dispersion, and catalytic performance of platinum nanoparticles supported on low-dimensional carbon materials. Platinum nanoparticles were deposited on graphene oxide derivatives and activated c...

Preparation-Dependent Structure and Selective Hydrogenation Performance of Pt Nanoparticles Supported on Low-Dimensional Carbon Materials

This preprint investigates the influence of preparation methodology on the structure, dispersion, and catalytic performance of platinum nanoparticles supported on low-dimensional carbon materials. Platinum nanoparticles were deposited on graphene oxide derivatives and activated c...