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Secure Your AI.
Before It Secures You.

AI systems introduce new attack vectors: prompt injection, model poisoning, data exfiltration, and autonomous agent exploitation. EyeR extends its autonomous detection, investigation, and response platform to your AI stack.

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Four Pillars of AI Security

Comprehensive protection for every layer of your AI stack.

Pillar 1

LLM Application Security

Protect applications built on GPT, Claude, Gemini, and open-source LLMs from prompt injection, jailbreaks, and data leakage.

Threat Vectors

Prompt injection attacks
Indirect prompt injection via documents
Model jailbreaking and constraint bypass
Sensitive data leakage in prompts
Training data extraction
Adversarial input manipulation

EyeR Protections

Input validation and sanitization
Output filtering and redaction
Context boundary enforcement
Prompt template lockdown
Real-time prompt monitoring
Anomaly detection on LLM behavior
Pillar 2

AI Agent Security

Monitor and control autonomous AI agents with tool-use capabilities. Prevent unauthorized actions and resource access.

Threat Vectors

Unauthorized tool execution
API abuse and over-provisioning
Agent goal manipulation
Excessive resource consumption
Cross-agent privilege escalation
Agent-to-agent attack chains

EyeR Protections

Tool use authorization policies
Agent behavior baselines
Action approval workflows
Resource quota enforcement
Agent sandboxing
Kill switches and rollback capabilities
Pillar 3

Model Supply Chain

Secure the entire AI model lifecycle: training data, model weights, fine-tuning processes, and deployment pipelines.

Threat Vectors

Training data poisoning
Model weight tampering
Backdoor insertion during fine-tuning
Supply chain compromise of base models
Malicious model updates
Unauthorized model exfiltration

EyeR Protections

Model provenance tracking
Training data integrity validation
Model weight cryptographic verification
Fine-tuning audit logs
Deployment pipeline security
Model version control and rollback
Pillar 4

AI Infrastructure

Protect GPU clusters, vector databases, model serving infrastructure, and AI workload orchestration platforms.

Threat Vectors

GPU resource hijacking
Vector database injection
Model serving API abuse
Unauthorized model inference
Training job manipulation
Infrastructure lateral movement

EyeR Protections

GPU workload monitoring
Vector database access controls
API rate limiting and authentication
Model serving isolation
Training job sandboxing
Infrastructure segmentation

Outcomes

What you get when you secure your AI with EyeR.

Deploy AI with Confidence

Ship LLM applications and AI agents without introducing new security blind spots. Maintain security posture as you scale AI adoption.

Prevent Data Leakage

Stop sensitive data from leaking through prompts, training data, or model outputs. Automatic redaction and filtering across all AI interactions.

Control Autonomous Agents

Set guardrails for AI agents with tool-use capabilities. Enforce authorization policies and prevent runaway automation.

Audit AI Behavior

Complete audit trails for every AI decision, action, and data access. Explainable AI security for compliance and forensics.

Secure the Supply Chain

Verify model provenance, validate training data integrity, and detect tampering across the entire AI lifecycle.

Monitor at Runtime

Real-time behavioral monitoring of AI systems in production. Detect anomalies, abuse, and exploitation as they happen.

Early Access

AI Security — Now Available

Join our early access program to help shape the product and get priority deployment.

Secure AI

Bring AI under the same security operating model

See how EyeR extends autonomous detection, investigation, and response to AI agents, LLM workflows, and model infrastructure.

Request an AI Security DemoSee the Platform