4.9

RAS Handling (Registry–Asset–Service)

Within a distributed intelligence network, coordination cannot rely solely on predefined services or static infrastructure configurations. Actors participating in the Internet of Intelligence must be able to discover capabilities dynamically, locate resources across the network, and assemble workflows using components that may exist anywhere within the infrastructure.

The RAS Handling subsystem — Registry, Asset, and Service Handling — provides the mechanisms that enable this dynamic capability discovery. It functions as the distributed knowledge layer of the infrastructure, maintaining awareness of what resources exist across the network and how those resources can be accessed.

In practical terms, RAS Handling allows the system to answer fundamental questions such as:

What AI capabilities exist within the network?
Where are these capabilities located?
Which runtime environments can execute them?
What infrastructure resources are available to support execution?

Without a structured discovery mechanism, actors would need to know in advance where specific services or assets are located. Such static configurations would severely limit the flexibility of the infrastructure and prevent the system from adapting to new participants or evolving capabilities.

RAS Handling therefore transforms the Internet of Intelligence into a self-describing system, where actors can locate services, assets, and execution environments dynamically as workflows are constructed.

The subsystem consists of three conceptual domains:

Registry — catalogs available capabilities and infrastructure components.
Assets — describes the resources and artifacts that can be used during execution.
Services — represents executable capabilities that actors can invoke within workflows.

Together, these domains form the capability discovery infrastructure that allows the system to operate as a distributed marketplace of intelligence services and computational resources.

Capability Registry

Distributed Catalog of Intelligence

At the core of the RAS subsystem lies the Capability Registry, which maintains a catalog of services, assets, and infrastructure resources available across the network.

The registry acts as a directory where infrastructure participants publish information about the capabilities they provide. These capabilities may include AI models, data processing pipelines, reasoning services, or infrastructure resources such as compute nodes and storage systems.

Each entry within the registry contains metadata describing the capability, including:

functional description of the capability
location of the service endpoint or asset
required runtime environment
resource requirements for execution
policy constraints governing its usage

This metadata allows actors and orchestration systems to identify capabilities that match the requirements of a particular task.

Unlike traditional service registries that operate within a single cluster or organization, the capability registry within the Internet of Intelligence is distributed across infrastructure domains. Multiple registry instances may exist across clusters or networks, synchronizing information through decentralized coordination mechanisms.

This distributed registry architecture ensures that capability discovery remains resilient and scalable as the infrastructure grows.

Asset Registry

Catalog of Resources

While the capability registry focuses on services that perform computation, the Asset Registry catalogs the resources that support those computations.

Assets represent the artifacts and resources that may be required during workflow execution. These assets may include:

trained AI models
datasets and knowledge bases
software packages or inference pipelines
configuration templates
infrastructure artifacts such as container images

Each asset is described by metadata that specifies how it can be accessed and what conditions govern its usage.

For example, an asset entry for a trained model may include information such as:

model architecture and version
required runtime framework
supported input formats
performance characteristics
licensing or policy constraints

By maintaining a structured catalog of assets, the system allows actors to discover the components required to assemble complex workflows.

The asset registry also enables version management, allowing multiple versions of models or datasets to coexist within the infrastructure. This capability is essential for experimentation, reproducibility, and continuous improvement of AI systems.

Service Registry

Executable Intelligence

While assets represent resources, services represent executable capabilities.

The Service Registry catalogs services that can be invoked during workflow execution. These services may include AI models exposed through inference APIs, data processing pipelines, reasoning engines, or specialized infrastructure services.

Each service entry includes metadata describing how the service can be invoked and what requirements must be satisfied before execution.

Service metadata may include information such as:

supported API interfaces
input and output schemas
runtime environment requirements
latency and throughput characteristics
security or policy constraints

This information allows orchestration systems to determine whether a particular service can fulfill the requirements of a workflow stage.

The service registry also supports dynamic service discovery, allowing actors to locate services that match specific functional requirements rather than relying on predetermined service endpoints.

For example, an orchestration system may search for a service capable of performing natural language inference. The registry can return multiple candidate services capable of fulfilling that role, allowing the orchestration system to select the most appropriate one based on performance or policy criteria.

Through this capability, the infrastructure becomes capable of composing workflows dynamically from available services across the network.

Metadata Layer

Semantic Capability Description

The effectiveness of the RAS subsystem depends heavily on the quality and structure of the metadata describing services and assets.

The Metadata Layer provides a standardized framework for describing capabilities in a way that orchestration systems can interpret automatically.

Metadata entries may describe several aspects of a capability, including:

functional semantics of the service
required input data formats
expected output structures
infrastructure dependencies
performance characteristics
policy or governance constraints

By standardizing how this information is expressed, the metadata layer allows orchestration systems to match tasks with suitable capabilities automatically.

For example, if a workflow requires a service capable of performing image classification, the orchestration system can search the registry for services whose metadata indicates support for that function.

Metadata also enables capability negotiation, where actors can evaluate multiple candidate services and select the one that best satisfies their operational requirements.

Through semantic descriptions of services and assets, the metadata layer enables the infrastructure to operate as a self-describing ecosystem of capabilities.

Registration Mechanisms

Publishing Capabilities

For the registry system to remain accurate and up to date, infrastructure participants must be able to publish information about the capabilities they provide.

The registration mechanism allows services, assets, and infrastructure resources to announce their presence within the system.

When a new capability becomes available—such as a newly trained model or a deployed inference service—it registers itself with the registry by submitting metadata describing its properties.

Registration events may occur during several stages of the capability lifecycle:

when new services are deployed
when infrastructure nodes join the network
when new assets are uploaded to the system
when existing capabilities are updated or retired

These updates ensure that the registry reflects the current state of the infrastructure.

Registration mechanisms may also include verification procedures that validate metadata submissions before they are accepted. These procedures help ensure that registry entries remain accurate and trustworthy.

Through continuous registration updates, the registry subsystem maintains a living catalog of capabilities across the distributed intelligence network.

Capability Discovery

Dynamic Lookup

Once capabilities have been registered, actors and orchestration systems must be able to locate them efficiently.

The Capability Discovery subsystem provides the mechanisms through which actors can query the registry and retrieve information about available services and assets.

Discovery queries may be based on various criteria, including:

functional capability requirements
resource requirements
policy constraints
geographic or network proximity

For example, an orchestration system may search for a service capable of performing text summarization with GPU acceleration. The discovery system can return a list of candidate services that match these criteria.

Discovery mechanisms allow workflows to be assembled dynamically by selecting components from the registry at runtime.

Through this process, the Internet of Intelligence becomes a capability-driven ecosystem, where workflows can adapt continuously as new services and assets become available.