To build an AI chatbot for your website, decide what it should handle, give it your own approved content to answer from, connect it to a language model, add a clear route to a human, then test it on real questions before launch. A chatbot is software that holds a conversation with a visitor, and a modern one uses a language model to understand free-text questions. The hard part is not the chat window. It is making sure answers come from your content and that customers can reach a person. Our chatbot service covers builds for Malta businesses.
What is a chatbot?
A chatbot answers messages in a conversation. Older ones followed scripted menus and keyword rules: press 1 for opening hours. An AI chatbot uses a language model such as Claude or GPT, so it can understand an unplanned question and reply in natural language. Used for support, it becomes AI customer service: it answers common questions, collects details, and passes anything complicated to staff. A chatbot mostly talks. An agent also takes actions in your systems, a difference we explain in AI agents vs chatbots.
How to make an AI chatbot: the steps
1. Scope it narrowly
List the ten to twenty questions your team answers most. Opening hours, delivery times, returns, how to book, what a service includes. Start with those. Also write down what the bot must never do: give legal or medical advice, promise refunds, quote prices you have not published.
2. Gather and clean your content
The chatbot is only as good as the material behind it. Collect your FAQs, policies, service descriptions and price lists. Remove outdated pages and contradictions first, because the bot will repeat them. Assign someone to keep the content current.
3. Use retrieval from your own documents
Do not rely on the model’s general knowledge. The standard method is retrieval-augmented generation: your documents are split into passages and indexed, and when a visitor asks something, the relevant passages are fetched and given to the model with an instruction to answer only from them. If nothing relevant is found, the bot should say it does not know and offer a human. This is the single biggest factor in avoiding invented answers. The LLM implementation guide explains the options in more detail. Our catalogue includes FAQ and knowledge base answer drafting for the staff-facing version.
4. Set tone and languages, including Maltese and English
Write a short style guide: formal or friendly, first-person or “we”, how it greets people. Customers in Malta often switch between Maltese and English in one message. Test both, and mixed messages. Language models handle English well, and Maltese less reliably, so check output with a native speaker before you promise Maltese support. If quality is uneven, say so in the bot’s behaviour: answer in the language you handle best and offer a person. Our bilingual customer communication drafting automation applies the same care to written replies.
5. Plan the handoff to humans
Decide when the bot stops: a complaint, a request it cannot answer, a visitor asking for a person, repeated confusion, or anything about payments or personal accounts. The handoff should pass the conversation history so the customer does not repeat themselves, and show opening hours if no one is available. Our chatbot-to-human handoff summarization automation produces a short summary for the agent who picks it up.
6. Test before launch
Write 50 to 100 real questions from your inbox, including awkward and hostile ones, and check each answer against your content. Try to make it say something it should not. Include misspellings, Maltese, and questions outside scope. Re-run the same set every time you change content or settings.
7. Measure after launch
Review actual conversations weekly at first. Useful measures: how many conversations the bot resolves without a person, how often it hands off, questions it could not answer (these show gaps in your content), and any customer complaints about it. Use these to update the content, not to tune the bot to look good.
Common mistakes
- Answers not grounded in your content. A bot that answers from general knowledge will eventually invent a policy. Restrict it to retrieved material and allow “I don’t know”.
- No escalation path. A bot that traps people is worse than no bot. Always offer a human route.
- Publishing before testing. A public chatbot’s mistakes are public.
- Ignoring GDPR and data handling. Chats often contain names, emails and order details. Tell visitors they are talking to a bot, say how their data is used, avoid collecting more than needed, set a retention period, and check where your chatbot provider and model provider process data and under what terms. In Malta the IDPC is the data protection authority. Confirm your specific obligations with your adviser, and see our GDPR and AI automation guide.
- Letting content go stale. Nobody owns the knowledge base, and the bot gives last year’s prices.
Website chatbot or WhatsApp bot?
A website chatbot reaches visitors who are browsing and have a question before they buy. A WhatsApp bot reaches customers where they already message, and suits bookings, order updates and follow-ups. WhatsApp automation needs the WhatsApp Business Platform rather than the free business app, and outbound messages generally need opted-in recipients and approved templates. Many businesses run both from the same knowledge base. Our guide to WhatsApp business automation in Malta goes into the setup, and the WhatsApp Business hub lists related work, including a WhatsApp AI customer service bot.
What about customer service automation more broadly?
Customer service automation includes more than chat: routing tickets, tagging, summarising threads, sending reminders. Often the quickest win is not the chatbot but the work behind it, such as channel-based ticket routing. An AI customer service agent goes a step further and can look up an order or change a booking, which needs tighter permissions and approval rules.
Frequently asked questions
What is a chatbot used for on a website?
Answering common questions, collecting enquiry details, booking appointments and directing visitors to the right page or person, at any hour.
How do I make an AI chatbot for my website?
Define a narrow scope, prepare your content, connect a language model with retrieval from your documents, add human handoff, test on real questions, and monitor after launch. You can use a hosted chatbot product or have one built.
Can an AI chatbot speak Maltese?
Language models can write Maltese, but quality is less consistent than English. Test with native speakers and have a fallback to English or a person.
Is an AI chatbot GDPR compliant?
That depends on how it is set up: what data it collects, where it is processed, retention, and the agreements with providers. Check with your adviser.
Where Automata fits
We build website and WhatsApp chatbots that answer from your own content, work in English and Maltese where quality allows, and hand over to your team with the conversation summarised. We also set up the monitoring that shows you which questions the bot could not answer.
If you want to see what this would look like for your business, get in touch.