Open Policy Agent, Cedar, OpenFGA and Oso answer one question well: may this principal do this operation on this resource. They are fast, general, and wired into enforcement points you build. Decionis answers a different one: may this exact consequential action execute now, under whose approval, and what happened afterwards — with the record signed. The shared word is authorization; the question, the moment, and the evidence are not the same.
the decision is about one business action rather than a permission: a payout, a refund, a limit change, an agent's tool call with an amount in it. You need the three outcomes — ALLOW, ESCALATE to a named person, BLOCK — evaluated on the action's own facts against your own policy, a single-use grant that executes once and cannot be replayed, and a signed Decision Dossier a counterparty or an auditor can re-derive without an account on your systems.
you are deciding who may reach what: service-to-service authorization, API and admin permissions, tenant isolation, relationship-based access over documents and projects, infrastructure and admission policy. Policy engines and authorization services are built for exactly that, evaluate in the path you deploy them in, and hold the permission model your application needed before any agent arrived. A decision gate is the wrong tool for a permission check on every read.
A policy engine's answer is a fact the authority evaluation reads, not a replacement for it. Keep OPA, Cedar, OpenFGA or Oso on who-may-reach-what, and put the execution gate on the actions whose failure you would have to explain: pass the permission decision in as evidence, let the gate evaluate the action's amount, counterparty and context against versioned policy, and let the dossier record both. An agent that holds a valid permission can still propose a wrong action; the gate refuses it for what it does, and the record shows which permission it held when it tried.
OPA is a CNCF-graduated, general-purpose policy engine: policies written in Rego are evaluated over structured input and return a decision document, with the engine embedded as a library or run as a server beside the service that enforces the answer. The enforcement point, any approval step and the record of what then executed are the integrator's to build.
Checked 2026-09-14 · Open Policy Agent — documentation (retrieved 14 Sep 2026)
Amazon Verified Permissions is a fully managed authorization service built on the Cedar policy language: fine-grained permissions over an application's principals, actions and resources, evaluated on request and kept outside application code. A held action, a named approver bound to it, and a signed record of the executed outcome are outside what the service describes.
Checked 2026-09-14 · Amazon Verified Permissions — product page (retrieved 14 Sep 2026)
OpenFGA is a relationship-based authorization system in the Zanzibar family: permissions are relationship tuples checked at request time, and its documentation lists patterns for AI agents, RAG and MCP servers alongside multi-tenant SaaS and microservices. It answers whether a caller may reach a resource; it does not hold an action, escalate to a person, or record what executed.
Checked 2026-09-14 · OpenFGA — documentation (retrieved 14 Sep 2026)
Oso positions 'Oso for Agents' as an AI agent security and control platform: approved AI traffic — prompts, tool calls and responses — brought under monitoring, on the premise that access models built for humans do not map cleanly to agents. That is access control and observation of agent traffic at the platform's own boundary; a per-action verdict with a named approver and a signed, externally verifiable record of the outcome is not what the page describes.
Checked 2026-09-14 · Oso — Oso for Agents (retrieved 14 Sep 2026)
Each of these is an input to the authority decision, not a substitute for it — see “Running both” above.
| Dimension | Decionis | Policy engines and authorization services |
|---|---|---|
| Question answered | May this specific action execute, now, under this policy — and under whose approval? | May this principal perform this operation on this resource? |
| Unit of decision | One intended action with its amount, target, counterparty and context. | A subject, an action and a resource, sometimes with relationships or attributes attached. |
| Outcomes | ALLOW, ESCALATE to a named person, or BLOCK — with reason codes. | Allow or deny. Some engines return a decision document or obligations; none holds an action for a person. |
| Where the evaluation happens | Outside the application that proposed the action, immediately before the commit, with a single-use grant claimed once. | Wherever you deploy the enforcement point — a sidecar, a library, a managed service — called by your code. |
| Human approval | Built in: the held action goes to an approver with the context attached, and nothing executes until they sign off on this action. | Out of scope: approval workflows live in your application or in another tool. |
| Evidence afterwards | A signed Decision Dossier per action — policy version, inputs, verdict, approver, outcome — verifiable by someone who does not run Decionis. | Decision logs inside your platform: what the engine returned, not what then executed. |
| Policy authorship | Business rules written by the people who own the risk, versioned, with shadow mode to see what would have been held before anything is enforced. | Rego, Cedar or relationship tuples, written and tested by engineers and deployed with the service. |
It is authorization of the agent's access, and you should keep it: an agent with no permission to reach the payments API is stopped there. It does not answer whether the specific payment the agent proposes should go out — the amount, the beneficiary whose details changed yesterday, the freeze window. That is a decision about the action, made at the commit, with a person pulled in when policy says so and a record signed afterwards. Run both, and feed the permission decision into the gate as evidence.
The category, in fullMany of them, yes, and a team that already has the engine wired in often does. What the engine cannot supply is the rest of the mechanism: the held state, the approver bound to this exact action, the single-use grant that executes once and cannot be replayed, and a signed record that stands outside your stack. Build those around the engine and you have built execution authority; Decionis ships it, and reads your engine's decision as one of its inputs.
Decionis vs Open Policy Agent, in detailPermissions describe what a principal may reach in general. An authorization boundary for tool execution sits between the agent and the tool and decides on each action as it is proposed, from outside the agent's process: it reads the permission model as one fact among several — the action's amount, its target, the approvals collected — returns ALLOW, ESCALATE or BLOCK, and leaves authorization evidence a reviewer can check afterwards. Agent-side guardrails are a third thing again: they shape what the model says, and an agent can reach the tool from outside them.
Decionis vs model guardrailsThe dossier records that this action was evaluated under this policy version with these inputs and this verdict, and who approved it. It is not a token that authorises anything: the authority to execute was a single-use grant, claimed once and spent. A relationship-based or attribute-based engine records the decision it returned; it has no view of whether the action then executed, or of what happened when it did.
What the dossier recordsRun a scenario in the sandbox and download the signed Decision Dossier it produces, or install shadow mode and watch what would have been held on your own traffic.
Start Now