Prompt injection defense
Detect instruction override, role escalation, system prompt extraction, and guardrail bypass attempts before they hit production agents.
AI agent security platform
Secure every prompt, response, and tool call.
AgentGuard gives AI engineering teams production-ready LLM guardrails for prompt injection defense, PII and secret detection, tool-call validation, remediation tracking, and audit-ready reporting.
- Secure API keys
- Project API keys are hashed at rest and shown only once on creation.
- Tenant isolation
- Supabase RLS keeps organizations, projects, logs, and reports isolated.
- Evidence-ready logs
- Every check records sanitized reasons, severity, risk score, and decision.
- Red-team validation
- Run adversarial test cases to catch guardrail gaps before release.
Input defense
Stop risky prompts at the gateway.
Inspect user input for jailbreaks, secrets, PII, and malformed payloads before traffic reaches your LLM.
5 SEC FLASH CARDBlock prompt injection before model calls
Security Platform
Details built for production AI teams.
Add guardrails without rewriting your whole AI stack. AgentGuard centralizes policy enforcement, logs, reports, and remediation in one workspace.
AI remediation advisor
Analyze recent guardrail logs with OpenAI-backed recommendations that avoid repeated or weaker policy suggestions after you apply a fix.
Resolution reporting
Track open findings, resolved findings, exceptions, retests, and resolution metrics from a single project view.
Live Guardrail Workflow
Watch every AI action move through policy.
The active policy gateway shows how AgentGuard inspects, scores, enforces, and resolves traffic as prompts, responses, and tool calls move through your application.
Active policy gateway
Block high-risk agent traffic
Inspect
Prompt, output, or tool call
Score
Scanner-specific severity
Enforce
Allow, flag, or block
Resolve
Reports and audit trail
SCANNERACTIVE POLICY
Pre-flight Input Shield
Intercept prompt injection, exposed credentials, PII, and malformed JSON before risky inputs reach an AI model.
METRICSScans before model calls
Low-overhead security verification runs before critical AI actions.
Pricing
Start small, scale into governed AI operations.
Starter
For builders validating guardrails on early AI workflows.
$0for evaluation
- 1 organization workspace
- 2 active projects
- Input, output, and tool-call checks
- Basic logs and policy editor
Team
For teams preparing production AI agents and compliance workflows.
$49per project / month
- Unlimited policy iterations
- Red-team module and reports
- Resolution tracking and exceptions
- AI Policy Advisor with OpenAI analysis
Enterprise
For organizations that need governance, rollout support, and review controls.
Customannual plans
- Custom scanner and policy workflows
- Security review support
- Advanced reporting requirements
- Deployment and onboarding assistance
Book Demo
Ready to make your AI agent safer this week?
Book a practical guardrail review. We will map your riskiest AI workflow, show the exact scanner coverage, and outline the fastest path to production-ready remediation and reports.
Book Demo- Map your AI agent risk surface
- Review guardrail scanner coverage
- Walk through logs, reports, and remediation
- Plan a secure pilot rollout
FAQ
Common questions before adding AI guardrails.
Where does AgentGuard sit in an AI workflow?
AgentGuard scans inputs, outputs, and tool-call payloads before risky content reaches models, users, databases, or third-party tools.
Does AgentGuard store prompts?
The product stores hashes, scanner reasons, severity, and decisions. It is designed to avoid caching private prompt content in persistent logs.
Can teams manage remediation after a finding?
Yes. The MVP includes policy editing, red-team checks, reports, finding remediation, exceptions, retesting, and AI policy recommendations.