Action first. Audit later.
AI agents execute sensitive tasks, then compliance teams discover gaps after risk has already moved through the institution.
OQIRON is the global AI agent trust institution — clearing agent actions against fixed policy before they are taken, and sealing each decision into a record that can be checked without trusting us.
Models can draft, decide, route, recommend, and act — but most enterprises still govern them through command centers, policies, approvals, and audits that sit outside the action path.
AI agents execute sensitive tasks, then compliance teams discover gaps after risk has already moved through the institution.
Every proposed agent action is intercepted, evaluated against policy, and cleared, escalated, or blocked before the action occurs.
The category shift is simple: move from retrospective AI governance to preventive AI infrastructure.
HUMAIN, Copilot, GPT, Claude, custom institutional agents, and future autonomous institutional systems.
The clearing engine that intercepts agent actions, evaluates policy, verifies authority, and generates evidence.
The systems that act: workflow agents, data requests, and regulated operations. MASSAR is the reference integration built against the rail.
This is a real record's shape, using real identifiers. It is an example printed on a page — nothing here is generated, and no decision is made by viewing it.
Sandbox access runs against the live rail on an isolated chain. Records seal to a separate genesis and never enter the anchored production chain. Access is granted manually — a person reviews each request.
Request sandbox accessA governance decision you cannot reconstruct is one you cannot defend. MURAQIB records every clearance as a tamper-evident artifact — so months later, an examiner can see exactly what was evaluated, which policy gates fired, and why the action was cleared, escalated, or blocked.
Follow any action from the moment it was proposed through every policy gate it passed, the authority that was checked, and the risk profile that was scored.
Reconstruct a past clearance exactly as it happened. Same inputs, same gates, same decision — a deterministic record, not a best-effort log.
Export a bilingual evidence pack aligned to the jurisdictions in scope, so a compliance team hands a regulator a document — not a database query.
MURAQIB exposes a structured clearance API that any enterprise system — SAP, Oracle, Microsoft, or custom — submits to before executing an AI action. The response includes the decision, evidence chain, and policy trace.
/clearance/evaluatePre-execution action clearance/agents/registerAgent identity and passport/evidence/{id}Retrieve evidence pack/policy-gates/simulatePolicy simulation/compliance/reportRegulator evidence packThere is no certification scheme for AI agents — ours or anyone’s. Nothing on this site certifies an agent, and no agent named here has been certified by anyone.
MURAQIB is the clearance rail. An agent declares a proposed action; the rail evaluates it against a fixed control catalogue and returns one verdict; the verdict and the declaration are sealed together into a hash-chained record.
MASSAR is the reference integration built against it — governed institutional request handling: classify, route, draft and escalate, with every action cleared by MURAQIB first. massar.oqiron.ai ↗
Every agent identity in production is governed by the rail. How many exist, how many hold a registered signing key, and how many hold an API credential are three different figures with three different dates — D2 carries each of them. One further identity runs in an isolated sandbox whose records seal to a separate chain and are not anchored.
Not certified agents. Not certification contracts. Institutions. Standards. Infrastructure. OQIRON is building the governance rail the agentic era will require — inspired by the institutional infrastructure that made global finance, standards, and safeguards interoperable — built from the Gulf, trusted by every side.