Use cases
AI Assistant for Compliance and Governance
A governed AI assistant for compliance gates every action behind human approval and records it in a full audit trail — every tool call, source, and sign-off on the record. Arlo resolves policy per run, holds writes and sends for a named reviewer, and exports the trail, so accountable teams can safely let AI act.
The thing that stops accountable teams from letting AI act isn't capability — it's not knowing what it will do, or being able to prove what it did. A governed AI assistant answers both. Every action is gated by a human approval, and every action is recorded in a full audit trail. That combination — approval before, record after — is what turns "we can't let AI touch that" into "we can, and here's the proof." Arlo is built this way by default: nothing that leaves a mark goes out until a person signs off, and nothing happens without a trace.
This is governance as a function, not a vertical. Whether you're in a regulated industry or just an accountability-heavy org where a wrong send is expensive, the shape is the same: a human check on consequential actions and a defensible record of every one.
Every action gated by approval
The moment an assistant can send, write, or spend, the question stops being "is it smart?" and becomes "what happens when it's wrong?" Arlo's answer is that consequential actions don't complete on their own. Anything that commits you pauses for the reviewer you name:
- Sends — an email, a message, a reply on your behalf.
- Writes — updating a record, editing a page, opening or closing a ticket.
- Spend and bookings — anything that costs money or commits an external party.
Read-only work — research, summaries, drafts you haven't asked it to send — flows without interruption. The gate lands only where the risk is, so review is a checkpoint, not a bottleneck. This is the same approval-before-sending model, made the default for governed work.
Policy resolves per run
Governance isn't a switch you flip after the fact — it shapes the run from the start. Before Arlo does anything, every tool connection resolves through policy: what it may touch and how far it can go. So the boundaries are decided up front, not discovered after an action already fired.
- Policy first. Each connection resolves through policy before the run begins.
- Act up to the line. Arlo reasons, drafts, and does read-only work on its own.
- Pause at the gate. Any send, write, or spend surfaces for the named reviewer.
- Record it. The action, its sources, and the approval all land in the trail.
A full, exportable audit trail
You can't govern what you can't see. Every run produces an audit trail: every tool call, every source it read, every human approval, tied back to the original request. Nothing is summarized away — the record is the actual sequence of what happened and why.
| Ungoverned AI assistant | Arlo | |
|---|---|---|
| Sends and writes by default | Acts on its own | Waits for approval |
| Who reviews risky actions | No one | A named reviewer |
| Policy on tools it can touch | Rare | Resolved before every run |
| Record of what happened | None | Full audit trail |
| Export for review or audit | No | Yes (Business plan) |
That trail is what makes AI usable where accountability matters. When someone asks what the assistant did — a manager, a client, an auditor — there's a complete, exportable record to show, not a black box.
Role-based access for accountable teams
Governance at team scale means the right people hold the right controls. On the Business plan, Arlo adds admin policy, role-based access, SSO, and audit export — so an administrator sets what the assistant may do, roles determine who can approve what, and the trail exports for review. The Team plan runs governance by default with per-run approvals and the full trace; Business adds the org-level controls.
Governance that supports compliance workflows
Rules like the EU AI Act phasing in through 2026 increasingly expect a human check on consequential automated actions and a record that one was in place. Arlo's approval gate plus audit trail is exactly that: a human in the loop before anything commits, and a defensible record after.
To be clear about what this is: these are governance controls that support your compliance workflows — a human-in-the-loop gate and a complete audit trail — not a claim of specific certifications. Arlo gives your team the mechanism to keep a person on every consequential action and to prove it happened. How that maps to your obligations is yours to define; Arlo makes it enforceable and recordable.
This is the AI colleague model with governance built in — across Slack, iMessage and SMS, Microsoft Teams, and live phone calls, working through 3,000+ tools and no-API browser use, all under the same gate and trail. See how it fits a single workday as an AI executive assistant, or browse more use cases.
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Last updated July 13, 2026