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Text channels · Knowledge base

AI chatbot development that answers and moves the process forward

We build AI chatbots that answer customer questions, qualify leads and provide support around the clock without tying up your team. We deploy them where your customers already are: on your website, in Messenger, on WhatsApp or in your helpdesk.

Definition

What is an AI chatbot in practice?

An AI chatbot is a virtual assistant that holds a text conversation with a customer or employee, draws on a knowledge base and can trigger the next steps of a process. It can answer a question, collect details, qualify a lead or hand the conversation over to a person.

A good chatbot does not pretend to know everything. We design it with a clearly defined scope, verified knowledge sources, escalation rules and integrations with the systems that take over the next step once the conversation ends.

Know the difference

AI chatbot, AI voicebot and AI agent are different solutions

The distinction matters because each one comes with different channels, risks, integrations and success metrics.

AI chatbot

Text conversation

Best for your website, Messenger, WhatsApp and helpdesk. Works well for FAQs, lead qualification and customer support in written channels.

AI voicebot

Phone conversation

Built for answering and placing calls, sending reminders, booking appointments and qualifying leads over the phone.

AI agent

Action inside the process

Goes beyond conversation: analyzes data, uses tools, runs workflows and creates tasks directly in connected systems.

Channels and use cases

Where can an AI chatbot really help?

The best chatbot use cases sit close to the customer — wherever questions repeat, details need to be collected quickly or a case must reach the right person.

Website

Website chat

The chatbot answers questions about your offer, collects contact details and qualifies visitors before they talk to your team.

Messenger

Social media inquiries

Instant replies, lead handoff to your CRM and escalation to a person when a decision is needed.

WhatsApp

Mobile-first customer contact

A convenient channel for quick questions, status checks, confirmations and first-line support.

Helpdesk

Ticket triage

The chatbot recognizes the topic, fills in missing information and routes the case to the right queue.

Knowledge base

Answers from your documentation

Responses come from a controlled knowledge base, which keeps them consistent and reduces the risk of made-up answers.

CRM

Lead qualification and handoff

After the conversation the chatbot sends the data to your CRM, adds a tag, creates a task or triggers a workflow in n8n.

Conversation safety

An AI chatbot needs boundaries, sources and escalation rules

Every implementation starts by agreeing what the chatbot may talk about, which knowledge base it uses, when it should admit it does not know the answer — and when it should pass the conversation to a person.

We design conversation logs, escalation rules, the scope of personal data processed (with GDPR in mind) and system integrations so the chatbot never makes decisions that belong to a human. Users are told they are talking to an AI assistant, in line with the transparency expectations of the EU AI Act.

Implementation process

How we implement an AI chatbot

A chatbot should be part of a process, not just a chat window. That is why the project covers content, channel, integrations, escalation and answer-quality measurement.

  1. 01

    Conversation scope

    We define the topics the chatbot covers, its knowledge sources, off-limits topics and the rules for escalating to a person.

  2. 02

    Channel and integrations

    We choose the channel — website, Messenger, WhatsApp or helpdesk — and connect it to your CRM, email or automation tools such as n8n.

  3. 03

    Quality testing

    We test answers on typical questions, edge cases and conversations that should trigger escalation.

  4. 04

    Monitoring and optimization

    We set up logs and metrics, review conversations, update the knowledge base and roll out further automation scenarios.

Integrations

Every chatbot conversation should end with a concrete action

  • OpenAI
  • Claude
  • n8n
  • CRM
  • Messenger
  • WhatsApp
  • Website chat
  • Helpdesk
  • Knowledge base
  • Email
  • Calendar

FAQ

AI chatbot FAQ

What is an AI chatbot for business?

It is a text-based assistant that answers customer questions using your knowledge base, collects details and can trigger the next steps of a process automatically. Unlike rule-based bots, it understands questions phrased in many different ways.

How is an AI chatbot different from a voicebot?

A chatbot works in text channels such as your website, Messenger or WhatsApp. A voicebot handles spoken phone conversations, which requires speech recognition, voice synthesis (for example with ElevenLabs) and real-time turn-taking.

Can an AI chatbot integrate with our CRM?

Yes. After a conversation it can create leads, add tags, save the conversation history, create tasks and trigger workflows, for example in n8n. That way a chat ends with a concrete next step rather than a transcript nobody reads.

Should a chatbot hand conversations over to a human?

Yes, and it is a key part of every implementation. Handoff is essential for complaints, sensitive topics, high purchase intent or whenever the chatbot is not confident in its answer.

How do you stop an AI chatbot from making things up?

We limit it to a controlled knowledge base, define topics it must not discuss and instruct it to admit when it does not know. We then test it on real questions and edge cases and keep reviewing conversation logs after launch to close gaps.

Your first AI chatbot

Let’s design a chatbot that answers and triggers the process

On a call we will agree on the channel, knowledge base, question scope, integrations and the moments when the chatbot should hand over to a person.

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