TheLLMstaysprobabilistic.Thebehaviorbecomescontrollable.
Plarix is the enforcement infrastructure that makes AI agent behavior controllable at the execution layer. Wyatt intercepts every tool call before it runs. Policy-based. Deny by default. Always on.
Runtime Enforcement for AI Agents
Thereisnoenforcementlayerbetweenwhatanagentdecidesandwhatitexecutes.
The agent acts, and you find out afterward. That is the current state of every major agent framework today.
No Enforcement Layer Exists
System prompts ask the model to behave. Output filters catch bad text after the model decides. Observability tools tell you what happened after the agent acted. None of these are enforcement. The action still executes — or already has.
Unpredictability Becomes Operational Risk
LLMs are probabilistic. They always produce unexpected outputs. When those outputs drive agents that take real actions — API calls, file writes, messages, purchases — unpredictability stops being a research problem and becomes a liability.
Enterprise Is Asking How You Control It
AI B2B SaaS companies with agents in production are stalling on enterprise deals because they have no infrastructure-level answer to: "How do you guarantee the agent stays in bounds?" A policy document is not an answer. Enforcement is.
TheAuthorizationGapIsReal
No major agent framework ships runtime enforcement. LangChain, CrewAI, AutoGen — zero. System prompts are not enforcement.
The execution-layer failure category. Your agent calls a tool it was not authorized to call. One action. Irreversible damage.
Wyatt intercepts every tool call before execution. Not sampled. Not filtered. Every call, every time, evaluated against policy.
Canonical Execution Event — structured logs that answer enterprise security questionnaires directly. What did it do, why, under what authority.
Your firewall cannot stop unauthorized tool calls. Your WAF cannot detect instruction hijacking. You need Wyatt.
AIAgentSecurityattheExecutionLayer
Wyatt is AI agent security infrastructure. It installs alongside any agent, intercepts every tool call, enforces policy, and logs every decision as a CEE audit record. Set it up and forget it exists.
HowWyattSecuresYourAIAgents
AI agent security requires enforcement at every layer — tool call authorization, context integrity, instruction validation, and static exposure detection. Wyatt covers all four.
AI Agent Policy Enforcement
Wyatt intercepts every tool call and enforces exactly what each AI agent is authorized to do. Not a suggestion. Actual enforcement — deny by default.
- Intercepts every tool call before execution
- Evaluates against declarative agent policy
- Blocks unauthorized actions deterministically
- Logs every decision as CEE audit record
Context Integrity Protection
Wyatt monitors what enters your agent's context and flags prompt injection and poisoned inputs before they corrupt behavior and drive unauthorized actions.
- Monitors RAG and context window inputs
- Detects prompt injection attempts
- Flags poisoned or manipulated data
- Prevents silent behavior corruption
Instruction Integrity
Wyatt validates that model output stays within authorized intent before the agent acts — blocking hijacked instruction sequences before they execute.
- Validates model output against authorized intent
- Blocks instruction hijack sequences
- Prevents agent from acting on injected instructions
- Reduces prompt injection attack surface
Wyscan — Free AI Agent Security Scanner
A free GitHub App that scans your LangChain, CrewAI, or custom agent codebase on every PR and reports unauthorized action exposures before they reach production.
- Scans on every pull request
- Reports exposures by AFB type
- Supports LangChain, CrewAI, MCP, AutoGen
- Zero cost — always free
GetStartedinThreeSteps
Add AI agent security without touching your existing stack. No rewrites. No framework changes. Wyatt runs alongside your agent — enforce, log, protect.
Install
One integration- Wyatt runs alongside your existing agent
- No framework changes required
- No rewrites needed
- One integration point
Define Policy
Simple declarations- Declare what each agent is permitted to do
- Specify allowed tools and resources
- Define permitted operations
- Wyatt enforces from the first run
Run and Forget
Always on- Every tool call intercepted automatically
- Every action evaluated against policy
- Every decision logged
- You do not manage Wyatt. Wyatt manages your agents.
AIAgentSecurityOutputsThatMatter
Enforcement is the core. But enterprise AI compliance requires proof — structured audit trails, real-time violation alerts, and AFB exposure reports that answer security reviews directly.
Complete Audit Logs
Every agent decision, timestamped and structured. Full visibility into what your agents are doing.
- Every tool call logged
- Timestamped decision records
- Structured for analysis
- Exportable audit trails
Real-Time Alerts
Know immediately when policy violations occur. No surprises.
- Instant violation notifications
- Configurable alert thresholds
- Integration with your stack
- Clear violation context
AFB Exposure Reports
Automated reports classifying your exposure by Agent Failure Boundary type.
- Generated automatically
- Classified by AFB type
- Prioritized remediation steps
- Track improvement over time
BuiltforAITeamsSellingtoEnterprise
If your AI agent has live tool access and enterprise buyers are asking how you control it — Wyatt is the answer. Not a policy doc. Actual enforcement.
AI B2B SaaS teams shipping agents to enterprise
Your agent is in production. It has tool access. Enterprise buyers are asking how you control what it can do. Wyatt answers that question with a tamper-evident audit trail and deterministic enforcement — not a policy document.
Teams moving agentic products upmarket
Your early customers loved the agent. Now enterprise is asking for SOC 2 evidence, incident response plans, and proof that your agent cannot go rogue. Wyatt gives you the infrastructure to pass that due diligence.
Engineers building agents that touch real data
Database access. API calls. File writes. Customer records. Your agent has the keys. One prompt injection, one malformed input, one instruction hijack — and it uses them wrong. Wyatt enforces the boundary at the execution layer, every time.
CoreGuarantees
Scanners tell you what is wrong. Guardrails filter text. Identity layers manage who can log in. Wyatt manages what the agent can do after it is already running — at the execution layer.
Framework Agnostic
Wyatt works with any agent stack. LangChain, CrewAI, LlamaIndex, MCP, custom agents. One integration. No rewrites. No framework changes.
Deny by Default Architecture
Nothing executes without explicit policy permission. Not configurable. It is the architecture. The only enforcement product built this way.
Built on the AFB Taxonomy
The only runtime enforcement product built from a first-principles security model of how agents actually fail — not a generic checklist ported from web security.
Virgil Attestation Layer
Every agent action gets a tamper-evident cryptographic record: action taken, policy matched, identity authorized, timestamp. Built for SOC 2, incident response, and enterprise due diligence.
Aryan Haghighi
Founder, Plarix
Solo founder. Electrical Engineering undergraduate at Bahcesehir University, Istanbul. Building runtime enforcement infrastructure for autonomous AI agents.
The thesis: a system prompt saying “do not delete files” is a suggestion, not enforcement. Wyatt is the first product built to close that gap deterministically — at the execution layer, before any tool call runs.
The Authorization Gap
Every major agent framework today relies on system prompts to constrain agent behavior. A prompt can say “do not exfiltrate user data.” The agent can still do it. There is no mechanism in any framework that deterministically stops it.
That gap — between what you instruct the agent to do and what it is physically capable of doing — is the Authorization Gap. It is the core attack surface for every production agentic system.
Plarix was built to close it. Wyatt intercepts at the execution layer. Before any tool call runs. Every time. Not a guardrail. Not a prompt. Deterministic enforcement.
CommonQuestions
How Wyatt enforces AI agent security at the execution layer — and why it works where guardrails, monitoring, and system prompts do not.
Cannot find what you are looking for? Reach out directly.
YourAgentsAreRunningRightNow
Nothing is enforcing what they can and cannot do. Wyatt changes that — runtime enforcement at the execution layer, deny by default, always on.
We are working directly with a small number of design partner teams — AI B2B SaaS companies with agents in production. Apply below and we will reach out within 24 hours.