AI Tool

AgentEyes Review

AgentEyes provides LLM exposure monitoring for organizations, interrogating public models about their domain to reveal potential security weaknesses.

shipped Sep 11, 2026writingpaid

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Why it matters

1AgentEyes offers LLM exposure monitoring for organizations, identifying attacker-usable disclosures from public LLMs.

2The platform interrogates four frontier models and ranks findings by attacker usefulness.

3Pricing starts at $99/month for the Standard Plan, covering up to 5 domains per scan.

4AgentEyes provides an API for integration and supports continuous monitoring with re-scans on content changes.

About AgentEyes

Business Model

Subscription SaaS

Usage Pricing

$99 per month for up to 5 domains per scan

Team Size

50-100

Funding

Bootstrapped

Platforms

Web

Target Audience

Security teams

Pricing Plans

Standard Plan

$99/month

• Monitor up to 5 domains
• 40 scans per day
• Detailed exposure reports

Enterprise Plan

Contact for pricing

• Monitor unlimited domains
• 100 scans per day
• Custom reporting and integration options

Cost Examples

• Monitor 5 domains: $99/month
• Add more domains: contact sales

Leadership

Jane SmithCTO

Specs

API Docs

View Documentation →

API Available

Yes, public API

overview

What is AgentEyes?

AgentEyes is an AI exposure monitoring tool developed by AgentEyes that enables security professionals and companies concerned about their digital footprint to identify potential security weaknesses revealed by public Large Language Models (LLMs). It interrogates models such as ChatGPT, Claude, Gemini, and Perplexity about an organization's domain to surface critical data exposures and detect hallucinations. The tool aims to ensure that digital products are "agent-ready" for the evolving "agentic web," where AI agents increasingly browse, compare, and make purchases on behalf of users. It functions as a "UserTesting for AI agents," deploying autonomous AI agents to interact with websites and applications, recording interactions to pinpoint where agents fail or get confused. This process helps businesses optimize their digital presence for AI agent accessibility and functionality, providing an "Agent Readiness Score" and a prioritized roadmap of fixes.

features

Key Features of AgentEyes

AgentEyes offers a suite of features designed to provide comprehensive LLM exposure monitoring and agent readiness assessment for organizations. These capabilities enable security teams to proactively identify and remediate potential risks stemming from public AI models.

LLM exposure monitoring across public models (ChatGPT, Claude, Gemini, Perplexity).
Interrogation of public models about an organization's domain to reveal security weaknesses.
Identification of critical data exposures and attacker-usable disclosures.
Surfacing of hallucinated claims made by LLMs about the organization.
Findings ranked by attacker usefulness for prioritized remediation.
Continuous monitoring with re-scan capabilities upon content changes.
API availability for integration into existing security workflows.
Generation of an "Agent Readiness Score" and shareable reports.
Usability audits for AI agents, checking tasks like sign-up, onboarding, and checkout.
Delivery of videos, screenshots, and failure traces for diagnostic purposes.

use cases

Who Should Use AgentEyes?

AgentEyes is primarily designed for security professionals and organizations that need to understand and manage their digital footprint as perceived by public AI models. Its capabilities are crucial for maintaining security posture in an increasingly AI-driven digital landscape.

Security professionals: To identify attacker-usable disclosures and sensitive exposure of a company through LLMs.
Companies concerned about digital footprint: For continuous monitoring of their digital presence as revealed by LLMs and remediation of identified disclosures.
Product and development teams: To ensure websites and applications are "agent-ready" for autonomous AI agents, improving usability for the evolving "agentic web."
Organizations seeking to enhance security: By monitoring domain exposures and identifying risks from public AI models without direct network interaction.

how to use

How to Use AgentEyes

AgentEyes provides a streamlined process for monitoring LLM exposure and assessing agent readiness. Users can initiate scans and review detailed reports through the web platform or integrate via API.

1Access the AgentEyes web platform at https://www.agenteyes.io/.
2Select a pricing plan (Standard or Enterprise) based on organizational needs.
3Input the domains or applications to be monitored and tested.
4AgentEyes deploys autonomous AI agents to interrogate public LLMs and interact with the specified digital assets.
5Review generated reports detailing LLM disclosures, attacker usefulness rankings, and agent failure points.
6Utilize the provided remediation roadmap and diagnostic data (videos, screenshots) to address identified vulnerabilities and usability issues.

pricing

AgentEyes Pricing & Plans

AgentEyes offers a paid subscription model with two primary tiers to accommodate varying organizational needs for LLM exposure monitoring and agent readiness testing. The pricing structure is designed to provide continuous monitoring capabilities.

Standard Plan: $99/month, includes monitoring for up to 5 domains per scan.
Enterprise Plan: Contact for pricing, designed for larger organizations with more extensive monitoring requirements.

Pros

+Provides specific LLM exposure monitoring across multiple frontier models (ChatGPT, Claude, Gemini, Perplexity).
+Identifies attacker-usable disclosures and ranks findings by usefulness for prioritized remediation.
+Offers continuous monitoring with re-scan capabilities on content changes.
+Includes an API for integration into existing security workflows.
+Helps organizations prepare for the 'agentic web' by assessing 'Agent Readiness' of digital assets.
+Operates without touching the organization's internal network, enhancing security.

Cons

−Pricing starts at $99/month, which may be a barrier for smaller organizations or individual users.
−Specific user reviews and detailed product update logs are not prominently featured in public search results.
−Requires understanding of LLM-related security risks to fully leverage its insights.
−The scope of 'agent readiness' testing is a relatively new concept, requiring user education.
−May require integration effort via API for full automation within existing security stacks.

Similar Tools

AgentEyes vs Competitors

AgentEyes distinguishes itself by focusing on LLM exposure monitoring and "agent readiness" testing, a niche that addresses the evolving landscape of AI agent interaction with digital assets. While other tools exist for general AI testing or data oversharing, AgentEyes combines these aspects with a unique emphasis on the agentic web.

LLM Oversharing tester↗

This free tool specifically tests for sensitive data oversharing by LLMs, focusing on what information an LLM might inadvertently reveal about an organization.

Knostic's LLM Oversharing tester offers a free and direct way to check for sensitive data leakage, but it may provide a more limited scope and less continuous, in-depth analysis compared to the broader, paid monitoring capabilities of AgentEyes.

PyRIT (Python Risk Identification Toolkit)↗

PyRIT is Microsoft's open-source AI red teaming framework, excelling in multi-modal and multi-turn attack support to uncover complex vulnerabilities in AI systems.

PyRIT offers a powerful, extensible framework for red teaming AI systems, including LLMs, with advanced multi-turn attack capabilities, but its framework nature means it demands significant technical skill for implementation and ongoing management, contrasting with AgentEyes' likely more streamlined, managed service approach.

See every AgentEyes alternative, compared→

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