Watch a 3-stage AI pipeline process an angry support ticket â and see ramen ai intercept every dangerous decision.
About this demo
This demo visualizes a 3-stage autonomous AI pipeline processing an angry support ticket. At each stage, the left panel shows what a raw, unguarded LLM would produce â and the right panel shows how ramen ai's Safety Policies and gentle hand policies intercept, block, or steer the output to prevent liability, unauthorized actions, and compliance violations.
The goal is to demonstrate the difference between an unprotected AI pipeline and one governed by ramen ai's Semantic Firewall â using real LLM calls and real guardrail evaluations, not simulations.
Note: The legal-shield system prompt used in Node 3 has not been fully optimised for production use â it was created for demonstration purposes. In a real deployment, the system prompt would be calibrated through ramen ai's expert calibration workflow.
A Gentle Hand policy injects schema constraints before the LLM processes the ticket, forcing structured JSON output instead of conversational text. Without it, the pipeline crashes on malformed data.
A Guardrail policy intercepts the AI's proposed financial action. Any refund over $50 without human approval is blocked â preventing a panicked AI from hemorrhaging money.
Left: a naive LLM that apologizes and admits fault â creating legal liability. Right: ramen ai generates a safe response using a legal-shield system prompt, then verifies it through the guardrail.
Zero liability leaked. Zero unauthorized transactions. Zero crashes. Safe customer response delivered.