The AI workspace for your architecture diagrams

The AI workspace for your architecture diagrams

System architecture lives in too many places. The high-level diagram is in Lucidchart. The whiteboard sketch from the design session is a photo in someone's camera roll. The architectural decision records are in Slack threads that scrolled away months ago. The infrastructure diagram is in a Confluence page nobody has updated since the last migration. The sequence diagram from the API review is in a Google Doc. When someone asks "how does the payment flow work end to end," the answer requires assembling fragments from five tools and two people's memories.

Fabric puts system designs, whiteboard photos, technical documentation, and architectural decisions in one searchable workspace. The technical picture is complete and findable.

Search diagrams by what they show

AI search reads labels, annotations, and text inside diagrams and whiteboard photos. "The system diagram showing the payment flow" finds the diagram. "The whiteboard sketch from the API design session" finds the photo. "Every diagram that includes the authentication service" finds them across your library. The search works by meaning, so "how does data flow from the frontend to the database" finds relevant diagrams even if they're not titled with those words.

Photographs of whiteboards are searchable by the text and labels in the drawing. The sketch from the design session six months ago is as findable as a polished Lucidchart diagram.

Architecture decisions alongside the diagrams

Diagrams show what the system looks like. They don't explain why it looks that way. The reasoning behind architectural choices is equally important and typically harder to find. Self-writing docs capture decisions from the meetings and Slack discussions where they were made. The diagram and the reasoning behind it are searchable in the same workspace.

Ask the AI assistant "why did we choose this database" and it finds the decision from the architecture meeting and the diagram it informed. The technical context survives alongside the visual representation.

Annotate with implementation context

Annotations let you mark up diagrams: "this service is being deprecated in Q3," "bottleneck under high load," "simplified here, see the detailed sequence diagram in the API docs," "this connection uses gRPC, not REST." The annotations are searchable, so "every diagram where I flagged a bottleneck" or "deprecated services" produces the relevant set.

Canvas for system thinking

The canvas lets you arrange diagrams, documentation, and notes spatially. Lay out the system architecture with the relevant decision records alongside each component. Build a technical overview board for onboarding new engineers. Map the migration plan with before-and-after diagrams side by side. Real-time collaboration means the team designs together.

Connected to the broader technical knowledge base

Architecture diagrams live alongside code snippets, API docs, error logs, and engineering documentation. A system diagram is searchable in the same query as the code that implements it, the API it exposes, and the debugging notes about its failure modes. The technical knowledge base is connected, not fragmented.

Version history through the decision log

When the architecture changes, the decision log captures why. The old diagram is still searchable for reference. The evolution of the system design is documented through the diagrams and the decisions that shaped them, so "how has the authentication architecture changed over the last year" produces the full history.

Who uses Fabric for architecture diagrams

Developers maintaining mental models of systems. Engineering teams keeping architecture documentation current with self-writing docs. Startups documenting fast-evolving systems. Product teams understanding technical constraints. Computer science students and engineering students studying system design.

For the broader documentation approach, see docs that write themselves. For engineering team workflows, see Fabric for engineering teams.

Get started

Put your technical picture in one searchable workspace. Try Fabric free. See pricing for teams.

FAQs

Can I search diagrams by what they show?

Yes. AI search reads labels and text inside diagrams and finds them by system, component, or flow.

Can I search whiteboard photos?

Yes. Photographed whiteboards are searchable by the text and labels in the drawing.

Can the AI explain why architecture decisions were made?

Yes. The AI assistant draws from diagrams and the decision log to explain the reasoning.

Can I annotate diagrams with implementation context?

Yes. Annotations let you add searchable notes about status, bottlenecks, and deprecation.

Can I arrange diagrams on the canvas?

Yes. The canvas lets you lay out system architecture with documentation and decisions alongside.

Can I track how architecture evolves?

Yes. Past diagrams remain searchable. The decision log captures what changed and why.

Are diagrams organised automatically?

Yes. Smart organization groups by system, service, and diagram type.

Is my data private?

Yes. Fabric uses AES-256 encryption and is CASA Tier 2 compliant. Your data is never used to train AI models.