The useful answer arrives too late
A live-chat team cannot cover every hour, every product, and every language. When the answer takes hours, the cart usually cools first.
Built for the moment your visitor is ready to ask.
Mikabot is a product-aware chat assistant for online stores. It reads the catalog, answers in the shopper's language, and turns hesitant browsing into a clearer buying path.
The purchase often breaks before checkout.
Most online stores lose intent in quiet places: a question sits unanswered, a support inbox fills with repeats, or search fails because the shopper does not know the store's vocabulary.
The team repeats itself all day
"Is this in stock?" "What size should I pick?" "Do you ship to Germany?" Those questions matter, but they should not consume the people needed for complex cases.
Search expects shoppers to know the answer
Keyword search is brittle when customers describe needs instead of product names. A good store needs guided discovery, not another empty result page.
It started inside a garden webshop.
In 2025 we put a Mikabot chatbot live on Arborix, a fast-growing garden and plant webshop. The first job was narrow: help visitors find the right plant by asking what they needed.
The chat quickly became more useful than the standard search bar. People asked for shade plants, pet-safe plants, gifts, and care advice in normal language.
That was the signal. The same pattern exists in fashion, electronics, furniture, food, services, and every catalog where the customer has a need before they have a product name.
Good product guidance shouldn’t need an enterprise budget.
We think every store deserves a sales assistant that actually knows its products, whether that store is a one-person Shopify shop or a multi-brand agency.
Most chatbots are FAQ pages with a chat bubble. Mikabot is built around the harder job: reading product data, asking useful follow-up questions, and recommending something the customer can buy.
The goal is practical: make strong product guidance affordable enough for normal stores, so owners can spend less time repeating answers and more time improving the business.
24/7 Always on
4 Languages
0 Lines of code to install
EU Built & hosted
How we decide what belongs in the product.
The operating principles behind Mikabot and Studio Mikado, the Belgian software studio that builds it.
AI where it is useful
Language models sit at the core of the product because conversation and product guidance need judgment. We do not add AI where a simpler rule would be better.
Built for catalogs
Mikabot is built for online stores, not retrofitted from a generic support desk. Stock, variants, descriptions, languages, and product links shape the product.
European by default
Belgian-built, EU-hosted, and designed with GDPR expectations in mind. Privacy and data boundaries are product requirements, not legal footnotes.
Close to the stores using it
We work with customers directly. The best improvements usually come from real conversations, awkward edge cases, and catalog details that did not fit the first model.
Outcome over novelty
A feature earns its place when it improves a business result: better answers, fewer repeats, clearer recommendations, or more useful analytics.
Launch is not the finish
Stores change. Catalogs grow. Traffic shifts. Mikabot is maintained as an operating product, not a one-time widget install.
Built by Studio Mikado
Mikabot is built and maintained by Studio Mikado, a Belgian software studio in Kortrijk. We build AI products for e-commerce as proper SaaS platforms, not one-off custom projects.
The stack is modern but proven: Laravel, PostgreSQL and OpenAI on the backend, with a lightweight vanilla-JavaScript widget on the storefront.
Mikabot is the studio's flagship and where most of our product time goes. We are a small team with a simple belief: capable AI sales tools should not be reserved for companies with enterprise budgets.
What that means
- A widget that works on any storefront without bringing a frontend framework along for the ride.
- Multi-language support shaped around European commerce from the start.
- Product work guided by store data, customer conversations, and real deployment constraints.