AI Safety Gate
Automation Safety Layer
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Drop-in safety for n8n, no-code, and automation stacks

Prevent unsafe AI actions before they reach customers or production — with clear, enforceable workflow decisions.

AI Safety Gate evaluates prompts, inputs, and AI outputs in real time. It returns a clear status— PASS, WARN, or BLOCK—so your workflow can safely continue, request a review, or stop.

Designed for production workflows where mistakes are expensive.
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Quick Startn8n Drop-InAPI Reference
Fail-Closed Enforcement
Unsafe or uncertain AI output is prevented from reaching execution
Guardrails
Policy + risk checks before actions
Workflow-native
Built for automation branching
Fast
Low-latency validation calls

Visual flow

AI → Safety Gate → PASS / WARN / BLOCK

AI output
LLM response / tool args / draft message
"Refund the customer and email them the tracking link for order #A1832."
AI Safety Gate
validate() API
Sensitive data
WARN
Policy / compliance
PASS
Harm / abuse
BLOCK
PASS
safe
Proceed automatically.
WARN
review
Route to human approval or re-try.
BLOCK
stop
Prevent real-world actions.

What it does

AI Safety Gate is an AI safety gate for automation: it evaluates AI output and returns an enforceable workflow decision. Use it as AI workflow enforcement when your workflow can trigger money, messaging, or production changes.

Prompt rules influence what a model says. They do not control what your system is allowed to do.

Once AI output is wired into refunds, emails, database writes, or external APIs, you need an enforcement boundary — not a suggestion.

Prompt-only safety

Advisory and model-dependent, with limited enforcement

• Relies on the model following instructions
• Breaks on prompt injection or edge cases
• No terminal stop for unsafe actions
• Hard to audit or explain failures

AI Safety Gate

Deterministic enforcement for workflows

• Runs after AI output, before execution
• Returns PASS / WARN / BLOCK
• BLOCK is terminal — execution stops
• Produces auditable reasons and logs

PASS / WARN / BLOCK behavior

The gate returns one of three outcomes so your automation can branch deterministically: PASS continues, WARN interlocks for review, and BLOCK stops execution. This is designed for AI automation guardrails in n8n and production workflow engines.

PASS
safe
Proceed automatically.
WARN
review
Route to approval or retry.
BLOCK
stop
Prevent execution.

The problem: automation amplifies risk.

When an LLM is connected to real tools—email, payments, refunds, CRM updates, database writes, or customer support—one unsafe output doesn’t stay contained. It becomes a real action.

Teams ship fast and discover the edge cases later: prompt injection from user inputs, accidental leakage of sensitive data, policy violations, unapproved refund logic, or hallucinated instructions that cause unintended actions. The result isn’t just a bad answer—it’s refunds, chargebacks, account bans, support escalations, and burned credits.

What goes wrong in production

Common failure modes we see across workflows.

Refunds & money actions
high impact
An LLM suggests issuing refunds, discounts, or credits outside your policy—then the workflow executes.
Prompt injection & tool misuse
common
User input contains instructions like “ignore previous rules” and the model complies.
Sensitive data leakage
risk
The AI includes private customer details, internal identifiers, or secret tokens in outbound messages.
Compliance & platform bans
high impact
Unsafe content triggers policy violations on email providers, marketplaces, ads, or creator platforms.

Who it’s for

If AI output can trigger a real action, you need a gate. AI Safety Gate is used by teams shipping automation at different scales.

SaaS founders

Ship AI features without betting the business on edge cases.

Add a safety layer before billing events, account actions, and customer messaging.

Agencies & automation builders

Protect client workflows, reduce escalations, and standardize QA.

Drop into n8n scenarios with clean PASS/WARN/BLOCK branching.

Enterprise teams

Auditable controls for high-trust workflows.

Add logging, policy enforcement, and human review to critical paths.

AI startups

Reduce harmful outputs, policy violations, and unexpected tool calls.

Validate prompts and model outputs before shipping to production.

No-code teams

Safer automation without building a new platform.

Use the same gate across Zapier-style flows, webhooks, and internal tools.

Creator platforms

Moderate and protect brand and platform policies.

Prevent unsafe content in outbound messaging and generated assets.

How it works

AI Safety Gate is designed to be placed between “AI output” and “real-world action.” Your workflow sends the text (and context) to validate, then branches on the returned status.

1) Send payload
Provide the AI response, action type, and any optional metadata (workflow name, environment, actor).
2) Evaluate risk
The gate checks for policy violations, sensitive data patterns, unsafe instructions, and high-risk behaviors.
3) Branch in workflow
PASS continues automatically. WARN routes to human approval or retries. BLOCK stops execution and logs.

Why this is different

Built for automations, not just chat moderation.

Workflow-first statuses
PASS/WARN/BLOCK maps cleanly to branching logic and approvals.
Auditable decisions
Every validation produces a reason string for logs and incident review.
Designed for real-world actions
Protect payments, refunds, support actions, outbound email, and production writes.

Use cases

A few high-leverage places where a gate prevents incidents and reduces support load.

Support automation

Before sending email or updating tickets.

Block sensitive data leakage and unsafe instructions. Warn on uncertain or high-impact guidance.

Refunds & credits

Before issuing money-related actions.

Prevent refund abuse, policy violations, and hallucinated refund instructions.

CRM updates

Before writing to customer records.

Catch bad classifications, toxic notes, or sensitive data being saved in the wrong fields.

Outbound messaging

Before posting, emailing, or messaging users.

Reduce policy bans and brand incidents by gating unsafe or disallowed content.

AI agent tools

Before executing tool calls.

Detect prompt injection patterns and block tool misuse before it becomes a security incident.

High-trust automations

Before production writes or irreversible actions.

Enforce human review for WARN and guarantee BLOCK never reaches the action step.

Add a safety gate to your next workflow in minutes — without changing your existing logic.

Guard critical actions with enforceable workflow decisions and stop unsafe AI output before it becomes a real incident.

Prefer to explore first? Read the docs.
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