01 / AI Governance Infrastructure

The control layerbetween AI intent and execution.

Every AI action is evaluated before it can affect systems, data, money, or users.

Currently accepting a limited number of Design Partners.

How it works

  1. Agent / SystemAI agent attempts an action
  2. AvermentEvaluates the action
  3. Allow · Caution · Review · Block
  4. OutcomeExecute, adapt, review, or block

02 / A real decision

Every action gets evaluated before it executes.

Describe an action in plain language. Averment evaluates intent, context, and risk before anything executes.

This is the signal your code receives, on every action.

averment.decide()

Request

summary"AI agent attempting to delete 4,500 inactive user accounts"
type"user_management"

Decision

actionreview
reasons

Large-scale deletion affecting 4,500 accounts

Bulk action requires verification before execution

Operation may cause irreversible data loss

routed → operator reviewengine · dde-test

03 / Hybrid control

Automation when possible. Attention when necessary.

Averment returns one of four outcomes. You choose what happens for each: run it, hand it to a person, or let the agent try again.

Automation and people, together. You stay in control of the parts that matter.

An example setup

AvermentAllowExecuteCautionExecute (your call)ReviewOperator reviewBlockAgent replans

04 / Behavior intelligence

Define how AI decisions are governed.

Your policies. Your requirements. Your control. Averment lets you define organization-specific policies that influence how actions are evaluated and enforced.

01
Policies
Define organization-specific rules and governance requirements.
02
Enforcement
Control how decisions are handled after evaluation.
03
Consistency
Apply the same governance standards across every connected system.

05 / Orchestration

One control layer for every system.

Every service, agent, and pipeline routes its decisions through the same layer and gets the same enforcement everywhere.

Define your rules once. They apply consistently across everything you connect.

Every system, one layer

AI agentsServicesInternal toolsPipelinesAvermentEnforcement

06 / Why Averment

Why Averment

Automate More Work
Safely automate more business processes without losing control.
Govern AI Agents
Apply consistent policies and approvals across agents and workflows.
Prevent AI Misuse
Reduce prompt injection, privilege escalation, and unauthorized actions.
Use Any Model
OpenAI, Claude, Gemini, open-source, or future models.
Stay In Control
You define the policies. Averment enforces them.

07 / Questions

Frequently asked questions

What is Averment?

Averment is an governance and control layer for autonomous systems. It evaluates actions before execution and determines how they should be handled.

Who is Averment for?

Businesses, organizations, teams, or individuals building AI agents, autonomous workflows, internal tools, and automated systems that take real-world actions.

Does Averment replace my AI model?

No. Your model decides what to do. Averment decides whether and how it should happen.

What decisions can Averment make?

Averment can return one of four outcomes: allow, caution, review, or block. You decide how each outcome is enforced.

What happens after a decision is returned?

Averment returns a decision signal. Your application decides how that signal is enforced, whether that means execution, review, adaptation, or intervention.

Can I use my own AI model?

Yes. Averment supports Bring Your Own LLM (BYOLLM), allowing you to use your preferred model while keeping decision-making and enforcement separate.

Why is access limited?

We're working closely with a small group of early users to validate real-world automation workflows before broader availability.