Bubo and Watermelon are both Dutch-built, EU-hosted AI tools that handle customer conversations automatically, but they answer a different question. Watermelon is an AI customer service platform — chat, email, WhatsApp and social media — built to resolve written conversations without a person. Bubo is an AI receptionist, built specifically to answer the phone itself. If your actual problem is a ringing phone nobody is picking up, that distinction matters more than any feature list.
Everything below about Watermelon comes from Watermelon's own website, checked in August 2026. Watermelon was not asked to review this comparison, and vendor pages change — check theirs directly before deciding.
What Watermelon actually is
Watermelon is a Utrecht-based company that has been building production software for more than ten years, offering a no-code AI Agent that handles customer questions across website chat, email, WhatsApp, Instagram and Messenger. According to Watermelon's own site, the AI Agent answers questions, carries out actions like order lookups and returns, and hands off to a person when judgement is needed — connecting to tools including Shopify, WooCommerce, Returnless and Monta to pull real-time data into its answers. Watermelon states it is trusted by 1,000+ companies, naming McDonald's, Greenwheels, KwikFit and AFAS among them, with published case studies claiming automation rates from 40% up to 98% of incoming conversations.
Watermelon's own channel list — website chat, email, WhatsApp, Instagram, Messenger and custom channels — does not include phone as a dedicated product channel with a page of its own, even though its homepage copy mentions "telefonie" among the channels an AI Agent can cover. What its published customer stories actually describe on this point is phone volume going down because customers are deflected to chat: KwikFit reports 30% less phone contact and Vintia an 80% drop in phone pressure, both attributed to the AI Agent handling questions on other channels before they become a call. That is a meaningfully different mechanism from a system that answers the phone.
Watermelon organises its solutions by team and by sector, naming e-commerce, healthcare, municipalities and government, education, and leisure and tourism — a notably different spread from Bubo's restaurants, trades and property focus, with government and education being sectors Bubo does not serve at all.
Where Bubo and Watermelon genuinely differ
Whether the phone itself gets answered. This is the central difference. Watermelon's product is a chat-and-messaging agent, and on its own published evidence its effect on phone volume is reduction through deflection rather than live voice handling. Bubo is built as a voice receptionist: it answers the ringing phone, holds a spoken conversation and finishes the job. A business whose core problem is unanswered calls needs the second kind of tool, not the first.
Vertical and scale positioning. Watermelon's client roster — McDonald's, AFAS, municipal governments — and its channel-based pricing point towards larger organisations with real digital-support volume across chat and email. Bubo is built around six small-to-midsize verticals (restaurants and hospitality, health and personal care, trades and automotive, property and professional services, retail and e-commerce, rentals), with the phone call as the starting point rather than one channel among several.
Finishing the transaction. Watermelon's stated strengths — order status, returns, resolving FAQs — are largely informational and post-purchase. Bubo's core mechanic is completing a transaction during the call: a reservation, a phone order, a deposit or a payment link over WhatsApp. And the parts that stop a busy service going wrong come with it — availability locked the instant it is checked, orders priced server-side and held for approval, approvals that time out rather than holding a table for nobody. These are different jobs rather than overlapping features.
Data and security. Both companies make a genuinely strong EU case. Watermelon states ISO 27001 certification with annual audits, EU-hosted data, end-to-end encryption and — a specific and useful claim — that customer data is never used to train external AI models. Bubo states EU-hosted data by default, isolation between businesses at the database level, masked phone numbers and no stored card data. Both are credible EU-first positions, and neither is obviously stronger than the other on what each publishes.
Pricing
Watermelon's own pricing page describes a free tier, then paid plans from around €99 a month (about €84 billed annually) for Starter, rising through Advanced and Business tiers to roughly €399–430 a month depending on the source consulted, billed by conversation volume — a "conversation" being all the messages exchanged with one visitor inside a 96-hour window, with add-on packs beyond a plan's limit. Watermelon states there is no cancellation period. Our own plans are on the pricing page.
Because Watermelon prices by conversations across channels and we price around call volume, the two do not meet on a single number. The useful exercise is your own chat and email volume against their tiers, and your own call volume against ours — a business might reasonably need one, the other, or both. The real cost of a missed call covers the phone side of that sum.
Which one actually fits your business
Watermelon is a strong fit for a business — particularly a larger one, or one in e-commerce, healthcare, education or the public sector — that wants written customer service automated across chat, email and WhatsApp, and is content for phone volume to be addressed indirectly by reducing how often anyone needs to call. Bubo is the better fit when the actual problem is calls ringing out or going to voicemail: a restaurant losing table bookings, a clinic missing appointment calls, a trades business missing an emergency callout.
For a business that genuinely needs both — written channels handled by one system, the phone by another — running them alongside each other rather than choosing between them may be the most accurate reading of this comparison. How to choose an AI phone answering service sets out what to test for on the phone side, and a demo is built around your own business.
Frequently asked questions
Is Watermelon GDPR compliant?
Yes, according to Watermelon's own materials, which state ISO 27001 certification with annual audits, EU-hosted data, end-to-end encryption, and that customer data is never used to train external AI models.
Can I use both Watermelon and Bubo together?
Functionally yes, since they cover different channels — Watermelon for chat, email and WhatsApp text, Bubo for the phone call itself. Nothing on either company's site suggests a conflict between running both, though we have not tested that combination directly.
Does Watermelon take payments or book appointments during a conversation?
Watermelon's own materials describe its AI Agent carrying out actions like order lookups and returns through integrations such as Shopify and Monta, but do not describe live appointment booking or in-conversation payment collection as stated features on the pages reviewed here. Confirm directly with Watermelon if this matters to you.
Can I switch from Watermelon to Bubo?
Since they are not the same category of product, "switching" may be the wrong frame — a business unhappy with its chat automation might add Bubo for phone coverage without cancelling Watermelon at all, depending on where the actual gap is.
Which one is cheaper?
They are priced around different units — conversations across channels for Watermelon, call volume for us — so a direct comparison is not meaningful without your own numbers on each. Watermelon's entry paid tier is stated around €99 a month; get a current quote from both against your actual usage.
Is this comparison biased, since it's published by phone-assistant.ai?
Reasonably assume some bias in any vendor-published comparison — which is why this piece states plainly that Watermelon is a well-established, credible platform with genuine strengths for the problem it is actually built to solve: broad channel coverage, a strong client roster, and a specific, verifiable claim about never training external models on customer data.