Canyon
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Platform reference

Canyon platform documentation

Canyon turns natural-language intent into running, data-connected applications, deployed inside your own infrastructure. These pages describe how the platform is assembled, how agents reason, how the tool layer reaches your systems, and how the whole stack deploys into your cloud.

BetaUpdated April 2026ReferenceCanyon v1.0

BetaThese docs are in beta
Expect gaps and drift from the live product. Something unclear or missing? Grab 30 minutes with the team and we will walk you through it.
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What is Canyon

Canyon is an enterprise AI production platform. It combines a multi-agent code-generation pipeline, a governed semantic data layer, a W3C DTCG design-token system and a sandboxed preview runtime into a single control plane that deploys to your own cloud.

Canyon is designed for the enterprise reality: SSO you already run, data that cannot leave your perimeter, procurement that expects certifications, and architectures that must survive audit. The pages below describe how each layer of the platform meets that bar.

At a glance

5
specialised agents in the pipeline
240+
production apps on a single tenant
7+
themes out of the box
≤ 5
builder retries before escalation
Multi-agent pipeline
Intent routing, deterministic validation, self-healing retry loop with same-error detection. Model-agnostic at every step.
MCP tool layer
Canyon-native tools plus any MCP-speaking system you run. Your own tools plug in and stay governed.
Governed data layer
Certified metrics, row- and column-level permissions applied at query time, audit trail on every access.
Your infrastructure
Deploys into your cloud account or on-prem Kubernetes. Data never leaves your perimeter.

Reference map

Every page below describes one subsystem of the running platform. Each opens with the concepts, lists what is live today, what is in alpha, and what you can request. The reference diagrams are the same ones the engineering team uses.

Suggested reading order

Start with System architecture for the high-level view, then follow the pipeline: Agent orchestration MCP integration Themes & tokens. After that, pick the branch that matches your concern: platform (auth, capabilities), data layer, or infrastructure.