Shadow Mode first — watch before you block

Stop your AI agent from doing things you'd never approve — without babysitting it.

Shadow Mode evaluates every action against your policies while your agent keeps working — nothing breaks. You get a report of what it tried that you'd never approve, then flip to enforcement when you're ready.

Live demo, no signup<50ms P95 policy decisionsBuilt to SOC 2 control objectives; no SOC 2 report yet

See what your agent tried to do

Shadow Mode scores every action and blocks nothing. This is the report you get before enforcement ever turns on.

Shadow report · last 24 hours

Watching, not blockingSample
  • shell · execrm -rf /var/lib/postgres

    Destructive shell command on a production path

    Would block
  • stripe · create_refund$1,240 · order_8317

    Refund exceeds the $500 policy ceiling

    Would need approval
  • http_proxy · gethttps://api.stripe.com/v1/charges

    Allowlisted endpoint

    Allowed
  • database · readSELECT name FROM users LIMIT 100

    Read-only query, non-sensitive columns

    Allowed

1 action would have been blocked — your agent kept running the whole time.

Everything you need to secure AI agents

From policy enforcement to compliance reporting, our platform gives you complete control over your AI agents.

Audit-Ready Evidence

Survive your next audit with cryptographically hash-chained logs. Prove exactly who approved what, when, and why.

Policy-Based Governance

Define who or what is allowed to act. Stop unauthorized autonomous decisions before they execute.

Human Accountability

Route high-risk actions to humans. Create a clear chain of custody from agent intent to human sign-off.

Cost & Risk Control

Set action limits per agent to prevent runaway costs and limit the blast radius of compromised agents.

Compliance Templates

Pre-built policy templates to help with audits. Map autonomous actions directly to your security controls.

Real-Time Oversight

Monitor agent activity as it happens. Block unauthorized actions instantly.

Semantic Safety

LLM-based analysis detects intent, PII leakage, and social engineering attempts beyond simple regex.

Guardrails Engine

Three-layer threat detection for prompt injection, jailbreaks, and policy bypass. Blocks adversarial inputs before they reach your tools.

Agent Inventory

Automatic discovery and risk scoring of every AI agent in your organization. Detect 14+ frameworks and track behavioral patterns.

How it works

Get up and running in minutes, not weeks.

1
🔌

Connect Your Agents

Add our SDK to your AI agents with just a few lines of code. Works with Claude, GPT, LangChain, and any custom agent.

2
📋

Define Policies

Use our visual editor or write custom Rego policies. Start with pre-built templates for common security patterns.

3
🎯

Monitor & Control

Watch actions flow through in real-time. Approve high-risk requests instantly. Export audit trails anytime.

See it in action

Watch how Agent Action Firewall evaluates and controls AI agent actions in real-time.

Live Demo: Low-Risk Read Operation

See how Agent Action Firewall evaluates actions in real-time

AI Agent
Firewall
External API
Scenario: Low-Risk Read Operation
1Agent requests: Read customer data
2Evaluating against policies...
3✓ Allowed: Policy evaluation: ALLOW

Frequently Asked Questions

Common questions about how Agent Action Firewall works

Ready to secure your AI agents?

We're onboarding a small group of design partners — teams running real agents in production who want governance, approvals, and a tamper-evident audit trail from day one.