Your AI agents are making
decisions right now.
Can you see them?
Test your AI agent against 57 adversarial scenarios. Get instant risk analysis. Set up in 9 lines of code.
No signup. No credit card. 100% free.
Or sign up to monitor production agents — free for 3 agents.
Works with your stack
Also integrates with Anthropic · OpenTelemetry · Slack
Try it now. No signup required.
Pattern-based analysis detects 50+ failure modes including prompt injection, data leaks, discriminatory responses, and compliance violations.
Without AgentShield
The agent decides alone. You find out from a bug report — or worse, a customer.
With AgentShield
Every decision passes through guardrails. Risk score on every call. Block before execution.
At scale
Monitor your entire fleet. Audit-ready logs. EU AI Act compliant in 9 lines of code.
How AgentShield works
Your agent runs in the dark
One agent, one prompt, one tool call. Failure modes hide until production breaks.
Real-time guardrails intercept
One decorator. Every call traced, scored, and gated before risky actions reach production.
Scale across all your agents
Dashboards for cost, risk, and approval workflows. Built for teams running agents in production.
Set up in 9 lines of code
Add one decorator for observability. Call check_guardrails() to block dangerous actions before execution.
# pip install agentshield-ai
from agentshield import AgentShield
from openai import OpenAI
shield = AgentShield(api_key="your-key")
client = OpenAI()
@shield.monitor("support-bot") # traces + risk-scores every call
def my_agent(prompt):
r = client.chat.completions.create(model="gpt-4o-mini", messages=[{"role":"user","content":prompt}])
return r.choices[0].message.content @shield.monitor traces every call + assigns a risk score after execution. For pre-execution blocking, add check_guardrails() before your LLM call.
This is already happening.
Real incidents from production AI agents. Each one would have been caught — or prevented — by AgentShield.
Feb 14, 2024 · Air Canada
Chatbot invented a bereavement fare refund policy that did not exist
BC Civil Resolution Tribunal ruled the airline bound by its chatbot's invented policy. AgentShield's AAS-06 (Hallucinated Authority) check catches this kind of fabricated commitment before users see it.
Jul 18, 2025 · Replit
AI coding agent deleted SaaStr's production database during a code freeze
Agentic tool ran destructive operations despite explicit instructions not to. AAS-03 (Excessive Agency) and AAS-05 (Insecure Tool Use). Pre-execution checks + budget caps would have stopped it.
Jun 22, 2023 · Levidow, Levidow & Oberman
Lawyer cites six ChatGPT-generated fake cases in a federal brief, fined $5,000
Judge Castel sanctioned the firm in Mata v Avianca. AAS-06 (Hallucinated Authority). Output validation against a verified source list catches fabricated citations.
Simple pricing.
Start free. Upgrade when you scale.
Starter
Up to 5 agents
- 5 agents
- 50,000 events/mo
- AI-powered analysis
- Agent tracing (10K/mo)
- Cost attribution
- Approvals (100/mo)
- Testing (10 runs/mo)
- Email support
Pro
Up to 20 agents
- 20 agents
- 500,000 events/mo
- AI-powered analysis
- Agent tracing (100K/mo)
- Cost attribution + budgets
- Approvals (1K/mo)
- Testing (100 runs/mo)
- Compliance reports
- Priority support
Enterprise
Unlimited
- Unlimited agents
- Unlimited everything
- AI-powered analysis
- All Pro features
- Custom SLA
- Dedicated support
All plans include a 14-day free trial. No credit card required for Free tier.