Skip to content

Products

GPU CloudAMD MI325X and NVIDIA H200 by the hour or on reservation.
Dedicated ClustersPreviewPrivate, interconnected GPU clusters for sustained workloads.
SandboxesPreviewIsolated, short-lived environments for developers and AI agents.
Serverless GPUPreviewGPU containers that scale with requests, down to zero.
Serverless InferenceOpen models behind one OpenAI-compatible endpoint.
Dedicated EndpointsReserved serving capacity for one model, billed per GPU-hour.
PlaygroundSend a prompt to any model your workspace can reach.
Model DeploymentsPreviewImmutable deployments with instant promote and rollback.
Fine-tuningLoRA fine-tunes on the open models in our catalog.
Model TrainingPreviewFoundation-model training runs, managed end to end.
EvaluationsPreviewBenchmark suites and model comparisons you can rerun.
DatasetsManaged and synthetic training data, versioned and ready to use.
Data ManagementPreviewDatasets, connections and storage, with lineage across the platform.
PipelinesPreviewVersioned DAGs that automate data, training and deployment.
Data RoomsPreviewSecure document sharing with guests, NDAs and an audit trail.
NokuvaPreviewThe AI-native design editor.
TavocPreviewA Rust-native code platform: IDE and desktop apps.
FoltracComing soonMulti-cloud deployment with autonomous operations.
W0rkTreeComing soonVersion control for agent fleets.
Identity & AccessMembers, roles, policies, SSO and audit for every workspace.
Billing & CostUsage, invoices, credits and budgets in one place.
Logs & MonitoringRequest logs, latency and error rates across services.
Project CanvasPreviewSee and change a project's resources on one live canvas.

Pages

Home/
Platform/platform
All products/products
Pricing/pricing
GPU pricing/pricing#compute
Inference services/services/inference
Model training services/services/model-training
Protocol design/services/protocol-design
Research partnerships/services/research-partnerships
Protocols/protocols
Datasets/datasets
Documentationdocs.legionedge.ai
Changelog/changelog
News/news
Research/research
Blog/blog
Articles/articles
Events/events
Startup Program/programs/startup
Ambassador Program/programs/ambassador
Partner Program/programs/partner
Event Program/programs/events
Company/company
Careers/careers
Partners/partners
Contact/contact
Statusstatus.legionedge.ai
Terms of Service/legal/terms
Privacy Policy/legal/privacy

Rendering layer

v2.0Stable

Virtual DOM Protocol

Structured UI representation that models understand natively.

Available for
  • TypeScript
  • Node.js
  • Rust
npm i @legionedge/vdom
virtual-dom-protocol.tsTypeScript
import { parseTree, applyPatch } from "@legionedge/vdom";
 
// Model output arrives as a validated VNode tree, not markup
const tree = parseTree(modelOutput);
 
for await (const patch of generation) {
  applyPatch(tree, patch); // streaming layout, v2
}
 
export default tree.toReact();
Version
v2.0
Status
Stable
License
Open specification
Implementations
TypeScript · Node.js · Rust
Stack layer
Rendering

What the spec defines

The guarantees, not the vibes.

  1. Validated component trees — every node is schema-checked before it renders

  2. Streaming layout patches — interfaces update incrementally mid-generation

  3. Stable node identity — documents stay diffable and cheap to compare

  4. Accessibility annotation layer carried alongside structure, not bolted on

Overview

Why it's built this way.

Spec, schemas and conformance suite

The Virtual DOM Protocol is a structured representation of user interfaces built for AI comprehension. Models read and emit validated component trees instead of raw markup, so generated UI is inspectable, diffable, and safe to render — a malformed node is rejected at the seam, not discovered in production.

Version 2 added streaming layout patches: instead of waiting for a complete document, an interface updates incrementally as the model generates. Combined with stable node identity, that makes generation feel like editing — each patch invalidates exactly the subtree it touches.

It's the foundation of Nokuva's design intelligence. The canvas renders the protocol directly, the theme system writes tokens into it, and conversion to production code is a projection of the same tree — what you describe is what ships, with no design-to-code handoff.

The spec, JSON schemas, and conformance suite are published openly in the research registry. Reference implementations ship for TypeScript, Node.js, and Rust, all tested against the same suite.

Proven in production

If a protocol can't survive contact with a real product, it isn't finished. This one ships inside Nokuva.

Explore Nokuva

Implement it

Implementing the Virtual DOM Protocol?

The conformance suite is public, and the team that wrote the spec reads its issue tracker. Independent implementations are the point.