AI Agents: Assistants That Take Action in Your Systems

AI agents are assistants that go beyond answering a question and carry out actions in your connected systems. An agent understands the customer's request, collects what it needs and completes the task with the tools you allow it to use: creating a record in your CRM, raising an appointment request, checking an order's status or assigning a support ticket to the right team.

How do AI agents differ from assistants?

A classic AI assistant gives information; an agent can also carry out several steps in order to reach a goal. For a customer who asks "can you move my Tuesday appointment to Thursday?", the agent first finds the existing appointment, checks the free slots, offers options and, once the customer confirms, sends the change. Each step is limited to predefined tools and to the permissions you set.

Which actions can be connected?

• Creating a new contact, opportunity or note in your CRM
• Raising an appointment or booking request, or passing on a change request
• Checking the status of an order, shipment or application
• Opening a support ticket and assigning it to the right team by topic
• Sending your team a notification or email under defined conditions

Which actions can be connected depends on the API or integration options of the systems you use. We plan these connections the same way as our business process and integration work.

You stay in control: permissions, approvals and logs

Letting AI agents change data in your systems calls for careful design. That is why every project follows these principles:

1. Least privilege: the agent reaches only the actions and data its task requires.
2. Approval steps: payments, cancellations, deletions or binding messages to customers need user or employee approval.
3. Action log: every action is logged with on whose behalf it was taken and which conversation led to it.
4. Failure handling: when a connected system does not respond or returns something unexpected, the agent does not pretend the task is done; it tells the user and passes the request to the team.

Working alongside automation

Classic automation runs on a predefined trigger and fixed steps; what happens is known in advance. An agent understands a request in natural language and decides which step is needed. So in most projects we use both: the agent understands the request and collects the details, and the action itself is completed reliably by a tested automation step.

Where to start?

For a first project we recommend one frequent action whose result is easy to check, such as an order status lookup or an appointment request. Once it has been verified with test scenarios and your team trusts it, further actions are added step by step. On the sales side, connecting what the agent collects to your CRM and sales systems is often a good first step.

Which businesses are they for?

Businesses where many customer requests turn into the same few actions benefit most: clinics and service businesses that work by appointment, online shops with many order and shipping questions, and organisations that run applications or registrations. In these businesses staff spend much of their time looking something up in one system to tell a customer, or entering a request into another.

If the systems to connect have no API, or the processes are not written down yet, that needs to be clarified first. In that case we map the process together and decide afterwards where the agent comes in.