NVIDIA Run:ai
NVIDIA Run:ai (formerly run.ai) is an AI operations and GPU orchestration platform for Kubernetes that pools, schedules, and governs GPU compute across clusters for training, fine-tuning, and inference workloads. It provides fractional GPU sharing, dynamic scheduling, quota and policy management, multi-tenant projects and departments, and workload lifecycle control across SaaS, self-hosted, and multi-tenant deployments. run.ai was founded in Israel, backed by Insight Partners and other investors, and acquired by NVIDIA in 2024; the product is now delivered as NVIDIA Run:ai. Its control-plane REST API exposes programmatic management of clusters, node pools, projects, departments, workloads (workspaces, trainings, inferences, distributed), assets, policies, permissions, service accounts, and audit logs, authenticated with bearer JWT access tokens obtained from client-credentials access keys.
Real signal across most facets with visible, nameable gaps — the contract exists but is thin, or the portal is good while governance and commercial terms are absent.
API Evangelist profiles NVIDIA Run:ai the way a machine reads it — 65 machine-readable artifacts across 62 APIs, pulled from the provider's own public surface and indexed so a developer, an analyst, or an AI agent can evaluate it against every other provider on the network.
Every provider in the network is reduced to the same set of machine-readable artifacts — OpenAPI contracts, event specifications, GraphQL schemas, runnable collections, pricing and rate-limit signals, security posture, OAuth scopes, and the agent surfaces (MCP servers and skills) that let software drive the API on its own. We profile them because the interface is the part of a company you can actually inspect: it is a truer signal of what a provider does than any marketing page. From those artifacts we compute the Kin Score — NVIDIA Run:ai scores 48.9/100 (developing), with a separate agent-readiness read of 51/100 (agent ready). The full breakdown is below, followed by every artifact we hold — each card links through to its machine-readable definition on apis.io.
Kin Score
This is the API Evangelist rating — a single, repeatable read computed from the artifacts on this page. Green fill is points earned; the red track is points possible, so every bar shows earned-versus-possible at a glance.
Kin Score
How this is scored →scored 2026-07-27 · rubric v0.5
How we profile NVIDIA Run:ai
Each block below is one kind of artifact we hold for NVIDIA Run:ai. For each we say what it is and why it earns a place in the profile, then list every one we've indexed — capped at two rows, scroll within the panel for the rest.
APIs 62
Each API is captured as its own OpenAPI definition — every operation, parameter, and response. This is the single most useful machine-readable description of what an API does, and it's what lets us score, lint, mock, and generate against it without asking the provider for anything.
Individual APIs this provider publishes, each with its own machine-readable definition.
NVIDIA Run:ai Access Keys API
Access Keys allow users to authenticate and interact programmatically with the NVIDIA Run:ai API. Each access key consists of a client ID and secret that can be used to obtain a...
NVIDIA Run:ai Access rules API
Access rules provide user authorization to system resources and entities. It is managed using Role-based access control (RBAC) which is a policy-neutral access control mechanism...
NVIDIA Run:ai Administrator Command Line Interface API
Information specific to the Administrator Command Line Interface.
NVIDIA Run:ai AI Applications API
AI Applications.
NVIDIA Run:ai Applications API
**DEPRECATED:** Applications have been renamed to Service Accounts. Please use the [Service Accounts](/latest/#tag/Service-Accounts) endpoints instead. Create and manage applica...
NVIDIA Run:ai AuditLogs API
The audit log provides audit trail information for user activity, changes to business objects and other important information. For more information, see [Audit log](https://run-...
NVIDIA Run:ai Clusters API
Use these endpoints to create, manage and delete NVIDIA Run:ai Kubernetes clusters.
NVIDIA Run:ai Compute API
A compute resource is a building block that represents compute resources such as GPUs, CPU cores, and CPU memory. The compute resources may consist of multiple physical resource...
NVIDIA Run:ai ConfigMap API
Use a ConfigMap as a data source location for data sets that are relevant to the workload being submitted.
NVIDIA Run:ai Credentials API
Credentials are used to unlock protected resources such as applications, containers, and other assets. For more information, see [Credentials](https://run-ai-docs.nvidia.com/saa...
NVIDIA Run:ai Datasources API
Data source assets.
NVIDIA Run:ai Datavolumes API
The Datavolumes API from NVIDIA Run:ai — 5 operation(s) for datavolumes.
NVIDIA Run:ai Departments API
Departments, in the hierarchy of resource allocation, are above Projects. A Department can contain multiple Projects, and has its own quotas. A Department's quota supersedes the...
NVIDIA Run:ai Distributed API
Distributed Training, is the ability to split the training of a model among multiple processors. It is often a necessity when multi-GPU training no longer applies; typically whe...
NVIDIA Run:ai Distributed Inferences API
Distributed inference enables running inference workloads across multiple pods, typically to scale model serving beyond a single container or node. This approach is useful when ...
NVIDIA Run:ai Environment API
An environment resource designates the container image, the image pull policy, working directory, security parameters, and others. It exposes all the necessary tools (open sourc...
NVIDIA Run:ai Events API
Workload events that occurred while the workload was running. Use to diagnose issue around workload scheduling.
NVIDIA Run:ai Git API
Use Git as a data source location for data sets that are relevant to the workload being submitted.
NVIDIA Run:ai HostPath API
Use a HostPath as a data source location for data sets that are relevant to the workload being submitted.
NVIDIA Run:ai Idps API
The Idps API from NVIDIA Run:ai — 3 operation(s) for idps.
NVIDIA Run:ai Inferences API
Inference workloads deploy trained models into a production environment to generate predictions from live data. These workloads are prioritized over Trainings and Workspaces dur...
NVIDIA Run:ai Logo API
Use to manage tenant logo files.
NVIDIA Run:ai Me API
"Me" returns the authenticated user's permissions within the system. It provides a comprehensive view of access rules (roles, subjects and scope) assigned to the current user. F...
NVIDIA Run:ai Network Topologies API
The Network Topologies API enables administrators to reflect the hierarchical network topology connectivity of nodes in a data center, such as racks, blocks, and other organizat...
NVIDIA Run:ai NFS API
Use NFS as a data source location for data sets that are relevant to the workload being submitted.
NVIDIA Run:ai NodePools API
Node pools assist in managing heterogeneous resources effectively. A node pool is a set of nodes grouped into a bucket of resources using a predefined (for example, GPU-Type) or...
NVIDIA Run:ai Nodes API
Nodes are worker machines in Kubernetes and may be either a virtual or a physical machine, depending on the cluster. Each Node is managed by the NVIDIA Run:ai control plane. For...
NVIDIA Run:ai Notification State API
Use to manage notification state.
NVIDIA Run:ai Notification Types API
Use to get notification types.
NVIDIA Run:ai NotificationChannels API
Notification Channels are the medium through which notifications are sent.
NVIDIA Run:ai NVIDIA NIM API
The NVIDIA NIM API provides endpoints to create and manage workloads that deploy NVIDIA Inference Microservices (NIM) through the NIM Operator. These workloads package optimized...
NVIDIA Run:ai Org unit API
Org unit.
NVIDIA Run:ai Permissions API
The Permissions API from NVIDIA Run:ai — 2 operation(s) for permissions.
NVIDIA Run:ai Pods API
Retrieve data about workload pods from your NVIDIA Run:ai platform.
NVIDIA Run:ai Policy API
Policies allow administrators to impose restrictions and set default values for researcher workloads. Restrictions and default values can be placed on CPUs, GPUs, and other reso...
NVIDIA Run:ai Projects API
Projects implement resource allocation policies and create segregation between different initiatives. It can represent a team, an individual, or an initiative that shares resour...
NVIDIA Run:ai PVC API
Use a PVC as a data source location for data sets that are relevant to the workload being submitted.
NVIDIA Run:ai Registry API
Use an images registry to enable the listting of repositories and tags that can be used as a data source location for data sets that are relevant to the workload being submitted.
NVIDIA Run:ai Reports API
The Reports API from NVIDIA Run:ai — 5 operation(s) for reports.
NVIDIA Run:ai Researcher Command Line Interface API
The Researcher Command Line Interface API from NVIDIA Run:ai — 9 operation(s) for researcher command line interface.
NVIDIA Run:ai Researcher Command Line Interface Deprecated API
The Researcher Command Line Interface Deprecated API from NVIDIA Run:ai — 9 operation(s) for researcher command line interface deprecated.
NVIDIA Run:ai Revisions API
Revisions are associated with an inference workload and represent a snapshot of its configuration. A revision is created on each change to the inference workload.
NVIDIA Run:ai Roles API
A role is a group of permissions that can be granted. Permissions are a set of actions that can be applied to entities. For more information, see [Roles](https://run-ai-docs.nvi...
NVIDIA Run:ai S3 API
Use an S3 simple storage service as a data source location for data sets that are relevant to the workload being submitted.
NVIDIA Run:ai Secret API
Use a credentials as a data source location for data sets that are relevant to the workload being submitted.
NVIDIA Run:ai Service Accounts API
Service accounts enable programmatic access to the NVIDIA Run:ai API, allowing applications or automated systems to authenticate and interact securely. Each service account is a...
NVIDIA Run:ai Settings API
View and manage configuration settings for your organization.
NVIDIA Run:ai Storage Class Configuration API
The storage class configuration API enables administrators to define, manage, and customize how storage classes are used across the NVIDIA Run:ai platform. Through this API, you...
NVIDIA Run:ai Storage Classes API
The Storage Classes API retrieves a list of available, pre-defined storage classes in the system.
NVIDIA Run:ai Subscriptions API
Use to manage notifications subscriptions.
NVIDIA Run:ai Template API
Templates are a pre-set configuration used to quickly configure and submit workloads using existing assets.
NVIDIA Run:ai Tenant API
Manage tenant settings.
NVIDIA Run:ai Tokens API
Use tokens to facilitate authentication to the NVIDIA Run:ai API. The API server must be configured to use the NVIDIA Run:ai identity service to validate authentication tokens.
NVIDIA Run:ai Trainings API
Trainings are dedicated workloads that are specifically used for training models. They are by design preemptible workloads because they are used in unattended sessions where the...
NVIDIA Run:ai User Applications API
**DEPRECATED:** User Applications have been renamed to Access Keys. Please use the [Access Keys](/latest/#tag/Access-Keys) endpoints instead. User Applications allow users to au...
NVIDIA Run:ai Users API
The Users API from NVIDIA Run:ai — 6 operation(s) for users.
NVIDIA Run:ai Workload properties API
Workload properties define the behavioral and scheduling characteristics of a workload submitted to the NVIDIA Run:ai platform. These properties such as type, category, and prio...
NVIDIA Run:ai Workload templates API
This set of endpoints manages workload templates used to define reusable workload configurations across various workload types in the NVIDIA Run:ai platform. Templates help stan...
NVIDIA Run:ai Workloads API
Workloads are both native platform workloads, Workspaces, Training and Inference, as well as workloads that originate from third-party ML frameworks, tools, or the broader Kuber...
NVIDIA Run:ai Workloads batch API
The Workloads batch API from NVIDIA Run:ai — 1 operation(s) for workloads batch.
NVIDIA Run:ai Workloads V2 API
The Workloads V2 API allows you to create, retrieve, and delete workloads that originate from third-party ML frameworks, tools, or the broader Kubernetes ecosystem. These worklo...
NVIDIA Run:ai Workspaces API
A Workspace is a simplified tool for researchers to conduct experiments, build AI models, access standard MLOps tools, and collaborate with their peers. Workspaces abstract comp...
Scroll within the panel for all 62 ·
MCP Servers 1
Model Context Protocol servers expose these APIs directly to AI agents. We profile them because agent-native access is the fastest-growing way this provider's capabilities actually get used.
Model Context Protocol servers that expose these APIs to AI agents.
runai-mcp.yml
MCP SERVERSecurity Posture 2
Authentication, domain security, vulnerability disclosure, and trust-center signals — the evidence that a provider takes security seriously enough to document it. We profile it because you can't govern what you can't see.
Authentication, domain security, vulnerability disclosure, and trust-center signals.
Resources
Every other property we hold for NVIDIA Run:ai — documentation, portals, status pages, policies, and corporate surface — grouped by the job it does, following the integrator's arc from getting started to running in production.
Get Started 3
Portal, sign-up, and the first successful call
Documentation 3
Reference material describing how the API behaves
Agent Surfaces 3
MCP servers, agent skills, and machine-readable catalogs
Design & Contract 5
Pagination, idempotency, versioning, errors, and events
Build 4
SDKs, sample code, and the tooling you integrate with
Access & Security 2
Authentication, authorization, and security posture
Operate 2
Status, limits, changes, and where to get help
Commercial 2
Pricing, plans, and the legal terms of use
Company 1
The organization behind the API
Other 1
Properties that don't map to a standard resource type
← All providers · Data indexed from github.com/api-evangelist/runai · machine-readable index on apis.io