Live System Visual Autoplay online

Ralphplan AI: Agentic RAG Memory + Digital Twin Edge System

A recruiter-facing system map that turns one static architecture diagram into a live operating surface: active memory lanes, agent handoffs, telemetry movement, evidence gates, and digital twin edge feedback cycling in real time.

Animated architecture map

How the system works

RAG Memory graph Edge loop Evidence
Ralphplan AI architecture diagram showing inputs, agent graph, memory layer, APIs, and digital twin edge loop.
Current focus

Inputs

Natural language prompts, documents, telemetry, and operator actions enter one governed system surface.

What viewers are seeing

One image, turned into a moving operations brief

The underlying architecture stays legible as a reference image while the interface adds motion only where it helps comprehension: focus transitions, data-flow traces, metric drift, and event narration. Claims stay honest: this page demonstrates the system shape and cycle logic, not an unverified provider path.

Data flow

Inputs, telemetry, and observations moving into reasoning and operator surfaces.

Context + LLM routing

Prompt assembly, model selection, and provider routing remain visible and bounded.

Memory access

Vector, graph, and event-memory layers show retrieval and state propagation.

Edge feedback

Telemetry, dashboards, anomaly scoring, and control loops stay in one narrative chain.