Case Study

Treyspace

Excalidraw with a chat sidebar that reads the board. The canvas is mirrored into HelixDB and clustered semantically, relationally and spatially, so the model traverses that graph through MCP tools instead of running flat vector search over the text. Open-sourced as an SDK.

Outcomes

Impact

Shipped to production on Azure and GCP, running real-time collaborative sessions for early users.
Built solo end-to-end over ten weeks: ingestion pipeline, GraphRAG, auth, and billing.

Stack

Tools

Decisions

Key decisions

Treating the canvas as the source of truth produced a much better UX than flattening content into plain notes.
Clustering based on proximity plus explicit links consistently beat semantic-only grouping.
Auth and billing had to be integrated into the core product flow to support onboarding and team usage.

Approach

Technical approach

Excalidraw events stream into a canvas-to-graph pipeline that builds semantic, relational, and spatial clusters.
Entities are synced into graph/vector storage so retrieval can use structure and not just raw text.
AI endpoints stream responses with board-aware context and links back to source nodes.
Collaboration and access control are handled through Supabase authentication.
Paid plans and recurring billing are managed through Stripe flows.

Visuals

Comparison