This page is designed to help you find out whether Otorize.AI is good and if it is the right choice for you.
AI agents (an n8n workflow, a bot, an assistant) work in a “room” alongside the team. They can talk and prepare work freely, but before doing anything real, like sending an invoice, refunding a customer or blocking an IP address, they ask first. otorize checks the request against the company’s rules: within the rules it goes through on its own, otherwise a person approves or rejects it with one click, even from email. Everything is kept on a tamper-proof record, ready for audit.
Listed in
Human approval, one click away
Agents propose; people decide. When an action needs a human, the right approvers get it in the app and by email with a clear summary, and approve or reject in one click. The email link is single-use and expires, and opening it alone decides nothing
Policy arbiter with adjustable autonomy
Choose how much each action may do on its own, per organization, room, case or agent: manual, supervised with a veto window, rule-based arbiter, autopilot, or confidence threshold. Rules check amounts, trusted lists, time windows and daily limits. Critical actions always go to a person, and anything unclear fails closed
Tamper-proof audit trail
Every message, proposal, decision and outcome is written to an append-only record, each event chained to the previous one by a cryptographic hash. Anyone with access can verify the chain in one click. The Decisions view filters every action and exports it to CSV for auditors
Works with the agents you already run
No SDK and no migration: an agent proposes with a single HTTPS call and can wait for the decision on the same call or get a signed webhook. It works with n8n, Make, LangGraph, OpenAI, Claude or your own scripts, and a built-in wizard generates a ready-to-import n8n workflow in seconds
5. Security and privacy by design
Messages, parameters and emails are encrypted with a separate key for each organization, and data stays in the EU. API keys are stored only as hashes and can be restricted to specific IP addresses. The rules read structured parameters only, never the chat, so a prompt-injected agent cannot talk its way past them
Most AI governance tools either watch agents after the fact or sit in front of the model as a filter. Otorize sits exactly where the risk is: between an agent’s intention and the real-world action. Agents work in a shared room with people and can talk freely, but anything with consequences (sending an invoice, issuing a refund, blocking an IP) becomes a structured proposal that must pass your rules or a human decision before it happens.
The approver reads a summary generated from the action’s parameters, never the agent’s own wording, and the rules engine reads only structured data, never the chat. A prompt-injected agent therefore cannot talk its way past them. Every step is written to a hash-chained record that anyone with access can verify.
It works with the agents you already have. One HTTPS call from n8n, Make, LangGraph, OpenAI, Claude or your own code. No SDK, no new agent framework, no migration. -Autonomy is adjustable per action. Manual, supervised with a veto window, rule-based arbiter, autopilot or confidence threshold, set per room, case or -agent. -Low-risk actions go through on their own; critical ones always reach a person. -Approvals are fast. One click in the app or straight from email, with single-use links. -Audit comes built in, not bolted on. A tamper-evident record, a one-click integrity check and a CSV export of every decision. It is built by security people. Per-organization encryption, data in the EU, IP-restricted keys, and rules that fail closed when anything is unclear.
Companies that are starting to let AI agents act on real systems and need to stay in control while they do it. Typically these are small and mid-sized businesses and enterprise teams in Europe, in three main roles:
Operations and finance teams automating invoicing, refunds and CRM updates. IT and security teams running SOC or patching automations. Automation builders who use n8n or Make for clients.
Behind them sit the people who must answer “who authorized this?”: CFOs, CISOs, compliance officers and auditors, especially under NIST, ISO 27001, SOC 2 and the EU AI Act’s human-oversight requirements.
Otorize was born at Zero Trust Systems, a cybersecurity consultancy in Italy, from conversations with clients who were connecting AI agents to their invoicing, CRM and security tools. The agents worked, but every pilot hit the same wall: “Who approved that action, under which rule, and can we prove it?”
The founder had seen how often automation outruns accountability. So instead of another chatbot, he built the missing layer: a place where agents and people work together, where the agents do the work and people keep the final say. The name says it: authorize, for the age of AI agents.
API: TypeScript stack on balanced cloud environments, with the Hono framework. Database: Cloud native DB, with row-level security for tenant isolation, append-only hash-chained event tables, and application-level envelope encryption (AES-GCM). Web app and website: React and Vite, hosted on Cloud behind a strict Content Security Policy.
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