Runtime Enforcement forAI Agents

The safety layer that stops unsafe actions—after AI decides, but before it executes.

enforce_policy.py

What Makes Safentic Different?

Action Interception

Intercept every agent tool call before execution

Policy Enforcement

Dynamic rules engine for real-time decisions

Audit Logging

Full action trail with decision context

Security Approach Comparison

Solution	Prompt Filtering	Action Blocking
Guardrails.ai	✔	✖
Calypso AI	✖	✖
Safentic	✔	✔

Why Runtime Protection Matters

Traditional AI safety stops at input validation. Safentic adds runtime action verification to prevent harmful executions.

Real-World Risk

•Unverified database writes
•Unfiltered API calls
•Unconstrained tool usage

Safentic Protection Flow

DecisionVerificationExecution

Sample Policy

{
  "action": "send_email",
  "conditions": [
    "user_verified: true",
    "contains_pii: false"
  ]
}

Try the Safentic SDK

Install Safentic from PyPI and block unsafe agent actions with one line.

pip install safentic

from safentic import SafetyLayer

      layer = SafetyLayer(agent=Agent(), api_key="demo-1234", agent_id="support_bot")

      layer.protect("send_email", {
          "body": "According to our refund policy..."
      })

      # [BLOCKED]: known false policy

Start Securing Your AI Agents

Schedule a call to learn about how Safentic can integrate with your AI agents.