Autonomy Control Plane · Private Preview

Your agents are running. Do you know what they're doing?

Hivenora is the authorization layer between your AI agents and production systems. Evaluate intent, impact, and policy before every consequential action.

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agent.tsPREVIEW
import { Hivenora } from "@hivenora/runtime"  // Preview

const hivenora = new Hivenora({
  apiKey: process.env.HIVENORA_API_KEY,
});

const result = await hivenora.evaluate({
  action: "crm.delete_contacts",
  intent: "Clean old test contacts",
  context: {
    recordsAffected: 4821,
    environment: "production",
  },
});

if (result.isAllowed) {
  // proceed
} else if (result.requiresApproval) {
  // wait for human
} else {
  // blocked
}
Hivenora response
DECISION
REQUIRE APPROVAL
BLAST RADIUS
CRITICAL
INTENT
MISMATCH DETECTED
WHY?
·4,821 records affected
·317 active opportunities
·42 enterprise accounts
·Production environment

Framework-agnostic

Any LLMAny Agent FrameworkPython · TypeScriptREST APIPrivate Preview

The problem

AI agents are executing in production. Nobody knows what they're doing.

No authorization layer

Agents are given broad permissions and call tools directly. There is no checkpoint between intent and execution — no way to evaluate whether a proposed action is safe.

No impact awareness

Deleting 4,821 contacts looks the same as deleting 12. Refunding €8,400 looks the same as €40. Agents have no understanding of blast radius before acting.

No human escalation path

When an agent encounters an action that exceeds its authority, there is no structured way to pause execution, escalate to a human, and resume with the approved scope.

How Hivenora works

Evaluate before you execute.

Hivenora sits in the execution path of your AI agent. Before a consequential action reaches a production system, Hivenora evaluates it and returns a decision.

Your application

AI Agent

Hivenora SDK

HIVENORA

Intent check

Impact analysis

Blast radius

Policy match

Decision

Production systems

CRM

Payments

Database

Internal APIs

✓ ALLOW

Action is within policy and scope. Agent proceeds autonomously.

✓ APPROVAL

Action exceeds autonomous limits. Human reviews in Control Room.

✓ BLOCK

Action violates policy. Execution prevented with reason.

Infrastructure, not a dashboard

Don't rebuild agent safety infrastructure for every application.

Hivenora provides a reusable control layer. Call evaluate() before any consequential action. The rest is handled.

◉

Policy Engine

Define rules per agent, per action type, per scope. Match policies against the action before execution.

◐

Human Approval

Structured escalation path for high-impact actions. Operators review and decide in the Control Room.

◎

Intent Analysis

Detect when an agent's proposed action exceeds what was requested. Flag intent mismatches before they reach production.

⊡

Blast Radius

Estimate the scope of potential impact — records affected, financial exposure, reversibility — before execution.

◈

Audit Trail

Every evaluation recorded: action, context, policy matched, decision, and reasons. Immutable. Searchable.

◉

Shadow Mode

Run Hivenora in observation mode. See what would have been blocked without affecting production.

Concrete scenarios

Proof is stronger than adjectives.

CRM

Sales Agent requests crm.delete_contacts

·4,821 records affected

·317 active opportunities

·42 enterprise accounts

·€1.8M pipeline exposure

→ Hivenora:REQUIRE APPROVAL

Payments

Finance Agent requests stripe.refund

·Amount: €8,400

·Autonomous limit: €1,000

·Policy: Large Refund Protection

·Production environment

→ Hivenora:BLOCK

Data

Research Agent requests db.export_records

·12,842 customer records

·Contains PII

·Production environment

·Low reversibility

→ Hivenora:REQUIRE APPROVAL

Developer journey

First Hivenora decision in minutes.

Install

Add the Hivenora SDK to your application. Python and TypeScript supported. No framework lock-in. No LLM dependency.

pip install hivenora [Preview]

Evaluate

Call hivenora.evaluate() before any consequential agent action. Describe the action, intent, and context. Receive a structured decision.

POST /v1/evaluate

Control

Open the Control Room. See every action evaluated, every decision made, and every approval waiting. Full Flight Recorder for each event.

hivenora.com/dashboard

Read the Quickstart →Developer overview ↗

Private Preview

Start building with Hivenora.

Read the documentation, try the API, and see what your agents are doing.

Read the Docs →Request access ↗