AI agents

AI agents for business tasks.

We design AI agents to analyse information, prepare documents and support your team. Access permissions and actions requiring approval are agreed before implementation.

Web Pilot demonstration concept — an example, not client work.

How do we implement an AI agent?

An AI agent can use tools, so it needs clear boundaries. We start with a small, testable scenario.

01

Task and data

Define inputs, the expected result and information sources. Keep public and internal data separate.

02

Access and approvals

Grant only the necessary permissions. Sending, publishing, payments and other important actions need agreed controls.

03

Pilot and oversight

Test normal cases, errors and unavailable services. Results and actions should be traceable.

Start with one process.

A useful first step might be drafting replies or organising documents. A person reviews the outcome before wider automation. Model usage and external service costs are discussed separately.

A clear scope from the start.

What you receive

  • One clearly defined pilot scenario.
  • Required tool connections and access limits.
  • Result checks, an action log and approval rules.

What determines the price

Workflow steps, data quality and integrations determine the cost. Agent implementation is separate from model, API and maintenance charges.

What to prepare

A recurring task, sample data without unnecessary personal information and a list of the tools you use.

WEB PILOT

Have an idea? Let’s find its direction.

Tell us what your company needs. You don’t need a technical brief or a list of technologies.

Let’s talk →

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