Describe a component in plain language. Completion Zone generates it using only tokens, variants, and patterns that already exist in your design system — no hallucinated styles, no drift.
Completion Zone is not a generic AI. Every generation pass is anchored to the full context of your Origin Graph — so the output is always on-system.
"Add a stats row below the chart" — your plain-language intent is parsed and the target artboard region is identified.
Natural languageRelevant components, design tokens, spacing scales, and color palettes are fetched from your Origin Graph and assembled into the model context.
Origin GraphClaude constrains its output strictly to the graph context — only existing variants, only tokens in your scale. No new styles are ever invented.
Constrained outputThe generated component is written into the artboard, the live canvas updates, and the result is emitted as an Intent Diff ready to ship.
Live ArtboardGeneric AI tools invent. Completion Zone finishes. The difference is the constraint layer: every output token is validated against your existing design system before anything touches the canvas.
Before Claude generates a single character, it receives the complete context of your Origin Graph — every token, every component name, every spacing value. The constraint is baked into the prompt, not tacked on afterward.
Completion Zone is not a thin wrapper around an LLM. It's a constraint engine built from the ground up for the specific demands of systematic design at scale.
Claude powers generation, but the constraint work happens before and after the API call. The system prompt is fully assembled from your Origin Graph on every request — no stale cached context, no drift over time.
Claude APIA validation layer sits between the LLM output and the canvas. Every proposed token value is checked against your design token registry. Invalid tokens are flagged or substituted with the nearest valid match from your scale.
Constraint layerThe Origin Graph is queried with a relevance function to fetch the most pertinent subset of your component library for each prompt — keeping the context window focused and the generation latency low.
Origin GraphBefore placing a completion on the canvas, Originmain diffs it against the current artboard state. Only the minimal set of changes is applied, producing a clean Intent Diff entry with zero noise or redundancy.
Intent DiffThe system prompt template communicates your design system's grammar to the model — token naming conventions, component composition patterns, spatial reasoning cues, and variant inheritance rules.
Prompt designAccepted completions are written back into the Origin Graph as accepted pattern examples. Over time, these examples shift the model's priors toward your team's specific conventions without any fine-tuning or retraining.
AdaptiveEvery piece of Originmain contributes to making completions possible — and every completion makes the rest of the platform smarter.
Early access is free. Connect your Origin Graph and run your first completion in under two minutes.