AI assistant for agencies — every client, one colleague

Agencies don't run on one client's problems. They run on twelve, all at once, held apart by whoever's paying attention that day. The status update to the retail account, the dev handoff for the fintech build, the PR client who wants a recap by Friday — the work is fine. The overhead of keeping it all straight, across a team, without the wires crossing, is what wears you down. An AI assistant for agencies takes that layer off the team. Arlo runs multi-client operations across iMessage and SMS, Slack, Microsoft Teams, and live phone calls, keeps each account separate, and routes anything client-facing through your approval first.

This is not the solo strategy setup — that's our AI assistant for consultants. An agency is multi-client and multi-person: five to twenty people sharing one operation, where one client's data must never surface in another's thread, and every account needs its own accountable record.

Client isolation by default

The fastest way to lose a client is to leak the wrong context into their conversation. Arlo holds per-client memory that stays walled off: the retail account's roadmap never bleeds into the fintech thread, and a draft for one client is built only from that client's context. Each account has its own scope, its own connected tools, and its own history, so the assistant reasons inside one client's world at a time.

That isolation is what makes shared access safe. A 5–20 person team can all delegate to the same assistant without anyone worrying that an account manager's request pulls up another team's client data.

Per-client context and memory

Running fifteen engagements means fifteen mental models nobody can hold at once. Arlo keeps persistent memory per account: the scope, the stakeholders, the decisions made, the deadlines, and where each thread actually stands. Every morning it posts one briefing of what moved overnight across every client — so the team walks in already knowing which accounts need attention.

When someone says "the campaign brief we sent them," Arlo already knows the client, the document, and what was last agreed. Nobody re-briefs it or scrolls back through three weeks of a Slack channel before replying.

Client updates drafted for approval

Client-facing comms are where trust lives, and one wrong send to the wrong account costs more than it saves. So nothing reaches a client unreviewed. Arlo drafts the update, the recap, the status note — and holds it for a named reviewer before it goes out.

• A client asks "where are we on the launch?" and Arlo assembles the status from Linear, Notion, and GitHub, then drafts the reply for an account lead to approve.
• A weekly client roll-up gets drafted per account, ready for the owner to sign off and send.
• A rescheduling request comes in over text; Arlo proposes times against the team calendar and confirms once approved.

You're still the name on every message. Arlo does the work; your team signs off.

Logging work across every client tool

The follow-through is the part that slips. Arlo connects to Gmail, Notion, Linear, GitHub, and 3,000+ other tools, so work lands in the systems each client runs on. It opens the ticket, updates the record, logs the hours, files the recap — scoped to the right account every time.

Some client tools have no API: the legacy portal, the homegrown dashboard. Arlo can log into those once in a secure browser session and read or update them the way a person would, under the same approvals and audit trail as everything else.

Governed access across the team

When five to twenty people share an assistant, governance can't be optional. Every connection resolves through policy before a run starts, every send or write waits for the reviewer you choose, and every account keeps its own audit trail — every tool call, source, and approval on the record, per client.

Action	What happens
Draft a client update	Held for a named reviewer before sending
Update a client's tool	Routed through policy, scoped to that account
Onboard a new client's toolset	Connected once, scoped, then available to the team
Every tool call and source	Logged in that client's audit trail

That per-client record is what makes agency work accountable: if a client asks what happened on their account, there's a full trace to show them. Arlo runs on prepaid credits — 400 credits per $1, starting at $50, and they last 12 months; admin policy, roles, SSO, and audit export are available on request for firms that need to govern the whole team.

Onboarding a new client

Winning an account shouldn't mean a week of setup. Point Arlo at the new client's tools — their Slack, their project tracker, their inbox — each connection scoped by policy up front. From there the team delegates to it the same way they'd loop in a coworker, and the new account gets its own isolated memory and audit trail from day one.

It's the same one-colleague model behind our AI assistant in Slack: one AI colleague, every surface, governed by default. Explore other setups in use cases.

Frequently asked questions

What does an AI assistant do for an agency? It runs multi-client operations at team scale — keeping each client's communications, context, and data separate while a 5–20 person team shares governed access. It remembers each account, drafts client updates for approval, logs work across client tools, and keeps a per-client audit trail.

How does an AI assistant keep client data separate? Client isolation is the default rather than a setting. Each engagement carries its own context and memory, and connections resolve through policy before a run, so work on one account doesn't leak into another.

Will it send things to clients without me seeing them first? No. Client-facing sends are held for a named reviewer. Arlo drafts the update, and it waits — nothing reaches a client until a person on your team approves it. See approval before sending.

Can the whole agency team use one assistant? Yes. Arlo is added once and the team reaches it in Slack, Microsoft Teams, or iMessage — no per-person app to install. Access to each client's tools is governed rather than shared wholesale.

Can it prove what it did on a client account? Yes. Every tool call, source, and approval lands in a per-client audit trail you can read back — which is what makes it defensible when a client asks who did what, and when.

What happens when we onboard a new client? You connect that client's tools and the assistant starts building context for the account from the first conversation, without mixing it into an existing engagement.

Try Arlo

Run your whole client roster through one governed AI colleague that keeps every account separate, remembers each engagement, and holds every client-facing send for approval. Get started.