AI Agents

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Web development

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App development

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AI agent

The customer service agent that answers from your knowledge

More than a chatbot with text blocks: the agent understands the request, finds the answer in your knowledge base, creates a ticket if needed and hands over with the full history to your team.

The agent identifies itself as AI – transparent and traceable.

Customer service agent

  • Answers only from your knowledge base
  • Source of the answer is traceable
  • Hand-off with conversation history
  • AI disclosure in chat
4–8 weeksto pilot start (guideline)
A personapproves what matters
Privacy-mindedbuilt with clear limits

Guideline values and concept – not results of real customers.

Dashboard view

Customer service agent: What the work looks like in the dashboard

Everything important at a glance: what the agent has handled, what needs your approval and what was handed to a person.

Standard questions at once, special cases handed over
Answers only from your knowledge base
Summary for your team included
History and sources traceable
Flow

Automatic where it is safe – with a person where it matters

Every step is visible and traceable. In special cases or when unsure, a person decides.

  1. 1Request comes inChat, email or form
  2. 2Understand the requestTopic and urgency
  3. 3Check the knowledge baseApproved sources only
  4. 4A person decidesSpecial cases and exceptionsA person decides
  5. 5Reply & logAnswer, note, history

Concept illustration. We define the exact flow together with you in the analysis call.

See the dashboard and flow for your case?

In the demo we show both using your processes – no obligation, 30 minutes.

Request a demo
Example

An everyday example

Invented dialogue for illustration.

  • Answer referring to your terms
  • Action after approval
  • Ticket for your team
Example chat
The agent identifies itself as an AI assistant.
CallerUntil when can I return my order?
AI agentAccording to your return policy, within 14 days of receipt. Shall I create a return label for you?
CallerYes, please.
Ticket created · label submitted for approval
Example viewInvented example
Clear boundaries

What the agent may do – and what not

The agent handles itself

  • Answer standard questions
  • Retrieve status and delivery info from your systems
  • Create tickets with all details
  • Categorise and prioritise requests

Submitted for approval

  • Goodwill and refund decisions
  • Answers outside the knowledge base
  • Escalations

Never does

  • Invent answers when the source is missing
  • Change or cancel contracts
  • Pose as a human
Integration

Where the agent can connect

  • Website chat
  • Email
  • Ticket system
  • Shop / ERP system
  • Knowledge base

Which systems can be connected is clarified in the analysis call – it depends on the interfaces of your software.

Use cases

Typical fields of use

Retail

Questions about delivery, returns and products.

Service providers

Appointment questions and status information.

Manufacturing

Spare-part requests and documentation.

Real estate

Questions from prospects and tenants.

Example calculation

Calculate with your own numbers

A thought model for standard requests.

Example calculation
Relief per month (hours)–
Calculated value per year–
Example calculation with freely editable assumptions – not a forecast and not a promise. Actual relief depends on your workflows; we work it out in the analysis.
Control & security

You stay in control

AI agents only work within the rules you define together with us.

People decide

Important steps are submitted for approval. You decide what may run automatically.

Traceable

Every action is logged so you can always see what happened.

Privacy from the start

Built with GDPR in mind: data minimisation, processing agreements and deletion concepts are planned from the beginning.

AI disclosure

Agents identify themselves as AI towards customers, as the EU AI Act (Art. 50) envisages for interaction with AI systems.

Legal requirements depend on the individual case. We do not replace legal advice.

Delivery

How the rollout works

Manageable, in stages, with clear decision points.

  1. Analysis

    Joint conversation, document the process, define goal and limits.

  2. Pilot · 4–8 weeks

    Limited deployment with real but non-critical cases.

  3. Go-live

    Step-by-step release, training, hand-off rules.

  4. Optimisation

    Evaluation, adjustment, controlled expansion.

FAQ

Answers to the most common questions

How is this different from a normal chatbot?

A classic chatbot follows fixed decision trees. The agent understands free text, searches your knowledge base and can trigger actions – for example creating a ticket. Decisive steps it submits for approval.

Can the agent say wrong things?

AI systems can be wrong. That is why the agent answers only from your reviewed knowledge base, names the source and hands over when unsure. We test this with your real questions before go-live.

How is the knowledge base maintained?

It stays in your hands. We set up a simple maintenance process and show how your team updates content.

What about privacy in chat?

We minimise collected data, point out the data processing in the chat and only load the agent after consent where required. We discuss details in the privacy concept.

Does it work by email too?

Yes. An email agent prepares replies; you decide whether they are sent automatically or submitted for approval.

Let’s talk through your case in 30 minutes.

We show you what an AI agent or software solution can take on in your business – and what it cannot. No obligation, no sales pressure.

  • Usually a reply within 1 business day
  • No sales pressure
  • A personal contact

We usually reply within 1 business day. * Required field

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