Platform · AI Assistant · AI Architecture Diagrams
Describe the system in plain language, or paste a photo of a whiteboard, and Design with AI draws it on a live canvas: trust boundaries, icon nodes, numbered flows, and a legend, laid out like a cloud reference architecture diagram. Not a static image, and not someone else's file format: real shapes that stay yours to edit.
Watch it work
One sentence in plain language becomes zones, services, datastores, flows, and trust boundaries: every shape a real, editable element on the canvas, not pixels in an image. Fix what the model got wrong, then carry the same diagram into the threat model and the design record.
On it: one trust boundary, six nodes, four numbered flows.
The definition
Draw this system: payments API behind the gateway, Postgres, Redis, and the settlement queue.
An AI architecture diagram generator turns a written description of a system into an architecture diagram. Most tools in this category produce a static image or a block of markup you paste somewhere else, which means the first time the design changes, you are back to redrawing by hand.
Alvor takes a different approach. The model supplies the structure: which zones exist, which nodes sit inside them, how the flows connect, and what the legend should say. The browser computes the geometry: grid-packed zones, ranked columns, orthogonal arrow routing. The model never invents pixel coordinates, which is why the output looks like an AWS or Azure reference architecture diagram rather than a scatter of boxes.
Because the result is real shapes on a live canvas, the diagram keeps working after the AI is done. Edit it by hand, ask for changes in place (the assistant reads the current canvas and your selection each turn), and carry it straight into threat modeling and the design document.
How it works
Type the architecture in plain language, or paste a whiteboard photo or screenshot and a vision-capable model recreates it as editable shapes.
Zones, icon nodes, numbered flows, and a legend appear on the canvas as the assistant works. The drawing is the preview; there is nothing to import.
Keep talking and it adjusts in place, scoped to your selection when shapes are selected. Or just drag things around: it is your diagram from the first shape.
The threat modeling studio reads this diagram, the design explanation is written against it, and the full design document exports as a PDF.
Semantic structure from the model, geometry from the browser: grid-packed zones, ranked columns, and orthogonal arrows, every time.
AWS, Azure, cloud, security, data, and developer icons. The catalog is injected into the prompt, so the model can only request icons that exist.
Flowcharts, sequence diagrams, ER models, state machines, gantt charts, and mindmaps render from Mermaid into the same editable shapes.
Paste a photo of a whiteboard or a legacy diagram and a vision-capable model rebuilds it as shapes you can actually maintain.
Align, distribute, group, and duplicate tools keep AI and human edits tidy without manual nudging.
The canvas autosaves as your diagram. There is no export step, no lock-in to a generated image, and no approval card needed: the drawing is the preview.
Bring your own model: Anthropic, OpenAI, Google, Azure OpenAI, Amazon Bedrock, or any OpenAI-compatible endpoint. Picture-to-diagram requires a vision-capable model.
Questions
Yes. In Alvor's Design with AI studio you describe the system in plain language, for example 'an ALB into two ECS services, RDS Postgres, and a Redis cache', and the assistant draws it on the live canvas: trust boundaries, icon nodes, numbered request flows, and a legend. The model decides the structure and the browser computes the layout, so the result reads like a cloud reference architecture diagram rather than a random arrangement of boxes.
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