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IN SHORT

One repeatable job.A human decision.

An AI employee prepares drafts, research or reports in a separate client environment. Start with a bounded workflow, approved sources and a named reviewer, not a broad assistant with undefined permissions.

Illustration of technical layers above dark stone.
Illustration, not a client measurement or an example of delivered work.
Which work can AI prepare for your review?

What work can a colleague check?

Preparing a response to an enquiry, gathering research or drafting a regular report can be a practical starting point. Describe what comes in, what a good result looks like and who approves it. Include the situations in which the assistant must stop and ask for help. Start with a bounded task before extending the role. If a source folder and a review queue solve the problem, the first version may not need any system integrations.

Approved knowledge, outside the chat.

Current prices, procedures, templates and examples of accepted work belong in maintained sources outside the conversation. We agree which document takes precedence when information conflicts, who updates it and how changes are recorded. A quick answer based on an old quotation is still wrong. The role should make missing information and assumptions visible to its reviewer.

Narrow access. A visible stop.

We document the providers, connections, permissions and data-processing arrangements before real client information enters the workflow. Access is limited to the selected task; a personal AI login is not silently turned into production infrastructure. Sending, publishing, deleting and changing customer records need their own controls and approval rules. We also agree what is logged, who can see it, how long it is kept and how access can be withdrawn.

Test before the routine changes.

We test representative examples, including incomplete or contradictory input, against acceptance criteria agreed with your team. In the first working loop, the assistant prepares output while your existing process remains authoritative. The handover covers the sources and instructions, access inventory, test cases, known limitations and a stop procedure. Adding a second workflow requires a new decision about scope and permissions.

Bring one task and real examples.

Bring two or three examples of the input, an output you would accept and the name of its reviewer. We turn that into a written scope covering the work, integrations, controls, acceptance test and price. For the Netherlands offer, onboarding starts at €1,500 once and the first AI role starts at €950 per month. A second role starts at €650 per month when the existing environment can be reused. These starting prices exclude VAT; the actual scope and ongoing terms are confirmed in the proposal. Nothing is connected before that scope and the relevant data-processing terms are approved.

The next step

Which work can AI prepare for your review?

All information

Explore the details at your own pace.

SERVICE · GSC.LOCALE.EQUIVALENTEnglish edition

An AI employee that prepares the work and leaves approval with your team

Not another empty chatbot account. We map one repeatable workflow, connect only the sources it needs and build a digital colleague that prepares drafts, research or reports in a separate client environment. Your team keeps the decision and the final send.

Discuss this with TheSEO ↓Read the Dutch source
One workflow firstA bounded task before a broad assistant
Separate environmentClient data and access stay scoped
Human approvalDrafting can be automated; accountability cannot
00 / ROUTE

How it works

A fixed route keeps the work reviewable. Each step produces input for the next one.

Choose the jobSelect recurring work with a clear input, output and owner.
Define the sourcesList what the assistant may read and what remains out of bounds.
Build and testRun real examples, record failures and add acceptance checks.
Hand over controlDocument access, review, logging, changes and the stop procedure.
01 / 05

Start with work, not with an AI personality

The useful question is not what an AI employee should be called. It is which repeatable job takes time every week and has a result a colleague can check. Sorting inbound requests, preparing a first research brief, drafting a report or turning meeting notes into actions are clearer starting points than ‘help the whole company’.

We describe the input, the allowed sources, the output format, the reviewer and the conditions under which the assistant must stop. That makes the first version smaller, but it also makes it possible to test. A broad assistant can look impressive while nobody knows when its answer is good enough.

02 / 05

Knowledge lives outside the chat

A working assistant needs approved context: procedures, templates, terminology, current prices and examples of accepted work. Those sources are versioned and separated from casual conversation. When a source changes, you can see what changed. When the answer relies on an assumption, the assistant has to say so.

We do not treat every document as equally trustworthy. A signed policy outranks an old note; a current price list outranks a previous proposal. The source hierarchy is part of the build, because a fast answer from the wrong document is still wrong.

03 / 05

Access is deliberately narrow

The environment is scoped to the client and to the selected workflow. Connections receive the minimum permissions needed. Secrets stay in provider-managed configuration, not in prompts or documents. Sensitive actions such as sending, publishing, deleting or changing a customer record require a separate control and, where appropriate, explicit human approval.

The operating design includes logs, rate limits, failure handling and a way to revoke access. An assistant should be able to explain which source it used, but logs should not become a second uncontrolled copy of every document. We agree retention and visibility before real data enters the workflow.

04 / 05

How the first production loop works

We first run a small set of representative examples, including awkward and incomplete inputs. Together we define what a pass looks like. The assistant then works in shadow mode: it prepares the output while your existing process remains authoritative. Only after the results are stable do we decide which step can become routine.

The handover includes the prompt and source structure, access inventory, test cases, known limitations and an emergency stop. You know what is running and who owns each connection. Expansion to a second workflow is a new decision, not an invisible extra permission.

05 / 05

Buying starts with a scoped intake

An AI employee is not a standard box that can be safely installed without seeing the workflow. The first conversation is therefore an intake, not a checkout pretending every implementation is the same. Bring one recurring task, two or three real examples and the name of the person who approves the result.

We then return a written scope with the sources, integrations, controls, acceptance test and current price. Nothing is connected until you approve that scope and the relevant data-processing terms. If the work does not need a custom assistant, we will say so.

FAQ

Questions before you start

Is an AI employee an autonomous agent?

It can prepare repeatable work, but autonomy is bounded per action. Sending, publishing and destructive changes need separate controls and often human approval.

Where is client information processed?

That depends on the approved providers and connections in the written scope. We document them before processing real client information.

Can it use our existing Claude account?

Potentially, if the account, permissions and data terms fit the workflow. A personal login is not silently reused as production infrastructure.

Can we start without integrations?

Yes. A source folder and a review queue are often the safest first version. Integrations are added only when they remove a proven bottleneck.

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AI and automationAI transparencyData processing agreementSub-processorsPricingContact
THESEO · 2017-2026

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