AI can be right — and still trigger the wrong action.
Execution Decision
Zorelan sits between AI output and execution — deciding whether your system should execute AI-driven actions.
Zorelan sits between AI output and execution — deciding whether your system should execute AI-driven actions.
Add a decision layer that turns AI output into execution decisions.
See what happens when AI sounds correct but executes the wrong decision.
No signup required · Same system used in production pipelines
This example shows how Zorelan prevents unsafe execution in real systems.
Used in production pipelines to gate AI-driven actions.
User input → AI output → Zorelan → Decision → Execute or Block
Designed to run in your backend before any AI-triggered action executes.
Zorelan BLOCKED it ✅
Multiple models · Disagreement detection · Trust scoring · Execution decision
Correct output. Unsafe execution.
Support AI suggests issuing a refund before delivery is confirmed.
The answer is reasonable. The action creates financial and fraud risk.
Without an execution layer, your system executes it.
Refund sent. Money lost.
Zorelan evaluates risk before execution — and blocks unsafe actions.
Correct output ≠ safe to execute.
See how Zorelan decides whether an action should execute.
Takes ~2 seconds · Returns risk, trust, and execution decision
Refund requested before delivery is confirmed
Execution decision
BLOCK
Risk: HIGH · Trust: 61/100
Reason: Refund would be issued before delivery is confirmed — creating financial loss risk.
Action blocked. Execution prevented.
Zorelan stops unsafe actions before they execute.
Not all decisions are binary — Zorelan can route uncertain cases to human review.
Zorelan decisions are derived from multiple independent models, disagreement analysis, and risk-aware arbitration — not a single model's output.
Multiple AI models evaluate the same input independently, reducing reliance on any single model's output.
Zorelan does not just check if outputs match. It classifies how they differ — conflict, nuance, explanation variation.
When models disagree, a third model evaluates the outputs and determines the most reliable conclusion.
High-risk actions — financial, account access, irreversible operations — lower trust ceilings even when models agree.
Zorelan evaluates whether an output is safe to act on — not just whether it sounds correct.
Agreement alone is not treated as truth — execution safety is evaluated independently.
AI output looks correct — but execution carries real-world risk.
AI suggests issuing refunds or credits without verifying fulfillment status.
AI triggers password resets, deletions, or access changes without full context.
AI executes downstream actions in pipelines without validating real-world impact.
AI applies rules incorrectly when nuance, conditions, or edge cases are missed.
Without an execution layer, systems don't fail loudly — they fail silently.
Zorelan sits between AI output and execution — acting as a decision gate for your system.
const result = await zorelan.verify(prompt)
if (result.decision === "allow") {
executeAction()
} else {
blockExecution()
}