QRION Agents · for IT and AI leadersEarly access

Bring your people's AI agents inside company rules.

Choose your models, share agents across teams, cap what each one can do, and keep the record. Agents that work inside your rules, not around them.

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What is QRION Agents?

QRION Agents is CoWorQ's agent governance layer. Instead of letting AI agents act with one person's credentials and no limits, it runs each agent as a bounded step inside a QRION workflow: the agent's authority is capped, an approval gate sits where the policy requires one, and its output is recorded with the reason and policy version. It works with any OpenAI-compatible model.

Status
Early access with design partners
Governs
Agent authority, approvals, usage and the record
Runs on
QRION workflows
Models
Any OpenAI-compatible model; no vendor lock-in

Pillar 2 · Governed by design

Your agents can act. Can they prove they were allowed to?

Personal agents have one principal, so they cannot model delegated authority or segregation of duties. Those are not missing features; they need an organizational process.

Personal AI agents compared with agents governed by QRION
DimensionPersonal AI agentsQRION Agents
Acts forOne person, with their credentialsA process, with each person’s authority
Decision basisRe-reasoned on every runDeterministic workflow; the agent is one bounded step
Approval modelThe user pre-authorizes action typesAuthority matrix enforced per transaction and per person
ExplainabilityA reasoning trace that varies run to runReason codes, weights and policy version
Cost per runModel inference every timeRules for routine decisions; inference only where needed
StateOne user’s session and memoryDurable waits across people and systems, for weeks if needed

The agent as a bounded node

The agent does the work. The workflow sets the limits.

An illustrative design: an agent drafts the review summary for a flagged order. It never decides alone.

  1. 1
    System step

    Order flagged

    A rule flags an order above the review threshold.

    Role
    QRION
  2. 2
    Agent step

    Agent drafts the summary

    Reads the history and writes a short case for the reviewer. Read-only access; output recorded.

    Role
    Capped agent
  3. Approval gate

    Reviewer decides

    A person approves or rejects, within their own authority limit.

    Role
    Review group
  4. 4
    System step

    Write-back and record

    Decision, agent output, reviewer and policy version, written to every system.

    Role
    QRION

What QRION Agents governs

Controls for agents at work

  • Authority caps

    Each agent acts within a limit set per step and per transaction, and cannot exceed it.

  • Approval gates

    Put a person where the policy requires one, with segregation of duties enforced.

  • A record of every action

    Agent output, reason, policy version and approver, kept with the transaction.

  • Model choice

    Any OpenAI-compatible model, chosen per team or per step, so you are never locked in.

  • Shared agents and skills

    Build an agent once in QRION Studio and reuse it across teams and workflows.

    Learn more

  • Usage you can see

    What each agent and team spends on models, visible before it scales.

Early access

Shape QRION Agents with us.

We are introducing agent steps with a small group of early-access customers. Tell us how your teams use AI agents today and where you need controls.

Prefer to start with a process? See the design-partner program.

We reply within one business day. See our privacy policy.

Questions

About QRION Agents

Is QRION Agents available today?

QRION Agents is in early access with design partners. QRION workflows, QRION Studio and Rigel are available now; agent steps inside running workflows are being introduced with early-access customers.

We plan to standardize on one AI vendor. Do we still need this?

Keep your vendor. QRION Agents adds the controls and portability around it: authority caps, approval gates, a record of every action, and the option to change models later.

Why not let a personal agent run the process?

A personal agent acts for one person with that person’s credentials. It cannot model delegated authority or segregation of duties, such as "this user may approve up to $25,000" or "the second approver must not be the first." Those rules need an organizational process.

How can we prove an agent was allowed to act?

Every agent step runs inside a QRION workflow with a capped authority. Its output is recorded with the reason, the policy version and the approver, so the record shows what was allowed and who allowed it.