Security and governance

Put AI agents into production without giving up control.

Governance starts before an AI agent runs. You define where it runs, what it may do, where a person approves, and how to stop it.

See it in action

Your agents, your systems, your credentials.

Your AI agents run in your environment, on your model account. They work with written instructions and only the access they need, and a named person approves every real action. That is the control framework for using AI under control.

RELIABL.IT does not connect to your systems. All the data it works with comes from the documents your users upload.

Your AI agents run on your side. The plan sits on the platform.

Two zones, and one control layer across both.

Your environment

Where your AI agents run.

  • Your AI agents
  • Your systems and data, with the access you approve
  • The people who use them
  • The actions the AI agents take

The RELIABL.IT platform

The planning layer. It does not connect to your systems.

  • The strategy and business documents you choose to upload
  • Stored encrypted
  • The plan, the reasons and the agent instructions

The control layer, across both zones

Human approvals Escalation rules Suspension procedures Monitoring

Human control is designed into the workflow.

Before an AI agent runs, its workflow defines these eight things in writing.

  • A named business owner
  • The agent's approved scope
  • The data and system access it requires
  • The actions the agent may take
  • The human approval points
  • The escalation conditions
  • The suspension procedures
  • The monitoring requirements

If the agent reaches a condition outside the agreed scope, the workflow stops, escalates, or asks for a person. It does not improvise.

Where a person stays in the loop.

One workflow, eight steps, and who owns each one.

  1. 01 People
    The business owner defines the priority and the scope.
  2. 02 AI agent
    The agent gathers approved context and prepares the work.
  3. 03 AI agent
    The agent drafts the outcome inside its guardrails.
  4. 04 People Approve
    A human approves before the action takes effect.
  5. 05 AI agent
    The agent executes the approved action and records it.
  6. 06 People Escalate
    An exception or low confidence is escalated to a person.
  7. 07 People Stop
    An out-of-scope condition stops or suspends the workflow.
  8. 08 People
    The owner reviews monitoring and the agreed measure.

An example of lanes and control points. Each workflow gets its own steps, approval points and escalation rules before an AI agent runs.

Human in the loop means that a person reviews or approves the actions you specify. Anything uncertain or out of scope goes to a person. The approval model changes only when you decide to change it.

How an AI agent reaches your files.

This is usually a practical question. The owner syncs the document library to their machine, puts the documents one workflow needs into a folder, and the AI agent reads that folder.

Nothing gets installed on your servers. If you want a direct connection later, it is a least-privilege account for named systems only.

Compliance depends on your use case.

Your legal, regulatory, security and industry obligations depend on your use case, your data, your deployment and the law that applies. RELIABL.IT makes no compliance claim on your behalf.

Methodology → What makes an AI agent governed → The platform →

Security and governance questions.

Where does our data actually go?

Your AI agents run in your environment, on your model account, under the data processing agreement you already have with that vendor.

RELIABL.IT does not connect to your systems. It works with the documents your users upload, stored encrypted. To read them and build the action plan, it uses external AI services.

Where does an AI agent run?

In your environment, on your credentials, with least-privilege access scoped to its workflow.

Your systems. Your credentials. Your agent. Only what it needs, nothing more.

Can an AI agent take real actions?

Yes, within the actions its instructions allow, and with a person who approves every real action on the early runs.

Approvals loosen only when you decide.

What happens if an AI agent is uncertain?

It stops and asks. The escalation conditions and the steps to suspend it are agreed before it runs.

It runs in a sandbox before it runs for real, and a person checks the output before anything reaches a customer.

Is RELIABL.IT compliant with GDPR, the EU AI Act, NIS2, DORA or ISO standards?

RELIABL.IT makes no compliance claim on your behalf. Compliance depends on your data, your use case, your deployment and the law that applies.

Your AI agents run on your side, access is least-privilege, the approval points are explicit, and RELIABL.IT does not connect to your systems.

See the approval points on an example company.

Every recommendation shows its reason, and nothing changes until a person approves it.

See it in action