Bhargav Attarde@Superawesomest

NodeDash turns a short admin interview into a company's live operating graph. Every node is a department rendered as a box on a hand-rolled, dependency-free Canvas physics graph, paired with an AI agent acting as its Chief of Staff. Edges carry approvals, materials, or data; agents negotiate along them, so a shift ripples through as a renegotiation, not a deadline surprise. The graph is public to view; clicking a dot opens a login modal where an access code claims a scoped seat (or admin opens everything), and the department docks open as a tab: responsibilities, workflows, documents, and a live agent chat. Auth is dependency-free (stdlib PBKDF2 + HS256 JWT). Onboarding is a 4-tier adaptive interview: macro defines the graph, micro defines nodes, workflow defines edges, AI agency defines guardrails. Generation self-heals, invalid LLM JSON gets one repair pass, then falls back to an offline mock so a demo never dies on a flaky model. Example: a vendor slips a checkpoint, its agent recomputes ETA and renegotiates with Procurement — updates ripple visibly, logged for audit. Every agent has RAG memory: similiarly-matched past exchanges, shown in chat as "recalled N past exchanges." One OpenAI-compatible client swaps between Ollama, Fireworks, and a self-hosted AMD MI300X (ROCm+vLLM) via one env var. (An optional production mode pairs an always-on fallback (Fireworks or DigitalOcean Gradient) with the on-demand MI300X it answers instantly while the GPU droplet wakes, then a watchdog destroys it after idling, so cost is zero when unused.) Built, not mocked: 39 offline smoke tests plus a RAG test, dependency-free auth, live graph editing, on-demand GPU orchestration, and a seeded workspace ~4,000 lines. Targets mid-market operators with vendor coordination. Seat-based SaaS per node, one workflow wedge before expanding. Website link - https://fisheries-bond-catalog-matrix.trycloudflare.com

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