Eevi, a voice-first AI language tutor, has raised a pre-seed round led by Rockstart. The Amsterdam-based company is building a language-learning platform built around spoken conversation, using real-time AI instead of the tap-and-swipe exercises that dominate the industry.
Filemon Schöffer and Jago Gazendam co-founded Eevi. Schöffer, the company’s CEO, previously co-founded Hubs.com, which Protolabs acquired in a transaction valued at up to $330 million, and later served as Chief Commercial Officer at European mental health platform OpenUp. He also co-authored The 3D Printing Handbook.
CTO Gazendam leads Eevi’s engineering and has a background spanning education and healthtech, having started his career integrating technology at NIST International School in Bangkok before founding several healthtech startups. Eevi marks Gazendam's return to the education sector.
I speak with Schöffer to learn more.
Why learning a language doesn’t mean you can speak it
Over a billion people are learning a new language right now. Few of them will ever reach conversational fluency. The most popular apps, such as Duolingo, have made language learning accessible and addictive. But they largely run on recognition: tapping translations, matching pictures, and dragging tiles into order.
Conversation, the skill learners want most, remains mostly untaught.
Eevi calls this the fluency illusion: you study a new language, build extensive streaks, then freeze the moment someone actually speaks to you.
The gap between recognising a language and actually speaking it is where the industry falls short
. Until now, the main alternative has been human tutors, which cost more and have limited availability. Eevi is betting that real-time voice AI can offer another approach.
“There are hundreds of millions of people trying to learn a second language, and only a small proportion will ultimately succeed. That's an enormous waste of human energy,” asserts Schöffer.
From frustrated language learner to founder
For Schöffer, language learning has long been in the back of his mind. “I've always been interested in teaching. My first company, when I was a teenager, was essentially an evening tutoring school for mathematics and physics.”
Even then, he found school to be a rigid, monotonous system.
“Now that I have children myself, I see that again. I've always been interested in how we teach people and how people actually learn.”
After he sold Hubs in 2021, he went to Japan and started learning Japanese.
“I experienced firsthand how limited the existing apps were,” he shared.
“I went to a language school, but I'm not particularly good at learning in group settings. I can't sit still! Again, I found myself thinking: somebody needs to fix this.”
His co-founder, Jago, is a childhood friend and a tech entrepreneur. After moving to Spain, he complained about the apps he was using to learn Spanish.
“We thought, with everything happening in AI, why don't we take a shot at language learning?”
They began work in the summer of 2025 and launched a closed beta in January. “Building a good first prototype took longer than I'd anticipated,” admitted Schöffer.
Beta testing pushed a voice-first interface
Eevi ran a six-month closed beta, from January to June 2026, with around a hundred advanced learners. According to Schöffer, one of the biggest lessons from beta testing was around the interface.
“Our original platform had the same basic chat interface as most LLMs. You could see a transcript of what you said and what Eevi said.
But we discovered that reading while you’re trying to speak isn’t actually a very good experience.”
That finding prompted the team to rebuild the interface around a more voice-first experience.
“Now you essentially have a blank canvas or whiteboard, and Eevi brings in supporting multimedia when it’s useful. For example, it might say, ‘We’ve practised these words, so now let’s practise listening to them,’ and bring an audio player onto the screen.”
The team developed a range of multimedia elements that Eevi can dynamically introduce to the whiteboard, rather than requiring learners to continually follow a written transcript.
“We didn’t know what a voice-first language-learning interface should look like when we started. Figuring out how it should work and feel was probably the biggest thing we learned during the beta.”
How Eevi works
Schöffer contends that while“Duolingo has added some speaking, but its core intellectual property is the curriculum it has spent years developing. It can't simply abandon that model.”
With Eevi, you open the app, and the tutor starts talking to you. Depending on your level, that might initially be in your native language or immediately in your target language. Eevi aims to recreate the experience of having a private language tutor, with the AI taking the learner through the lesson.
“It might say, ‘This is your first Japanese lesson. Let's learn how to introduce yourself.’ It can explain that there are different ways to introduce yourself in Japanese and provide the context for why, and then you actually have that conversation. “From there, it's voice-first.”
Eevi’s curriculum draws on more than 15 academic frameworks in language-learning research and covers more than 150 dynamic topics and situations, from family life and grocery shopping to dining out. Rather than emphasising grammar and memorisation, the team has focused on how quickly learners can apply what they learn. The curriculum is built around vocabulary and common sentences in context.
Eevi says roughly 500 words, mastered in context, cover about 80 per cent of daily conversation.
A personal tutor in your pocket
Schöffer has long believed that collective learning is fundamentally one-size-fits-all, and that this model is outdated.
“I have this slightly cartoonish view that everybody will have a personal tutor in their pocket. Language learning is commercially attractive, so I think it's one of the first skills where we'll see this happen. Whenever we build something new for the Eevi curriculum, I ask myself: if this were physics, would this approach still work?”
While you learn a new language, Eevi learns about you. Each conversation builds a clearer picture of your challenges and interests, helping shape what comes next.
“Currently, during onboarding, you tell us roughly what your level is. You can use the European CEFR system, for example, or indicate whether you're a beginner,” Schöffer explained.
As learners complete lessons, Eevi tracks what it has taught them and how they responded.
The company has built an individual memory for each user, which Schöffer sees as added value compared with simply practising with a general-purpose chatbot.
It plans to take this further with a conversational intake. Rather than telling Eevi your level, your first interaction would be a conversation in which it asks questions in your target language, listens to your answers, and dynamically assesses your ability. Schöffer also sees AI's ability to personalise learning at scale as one of its biggest advantages over a fixed curriculum.
“If you tell Eevi, ‘This is going too slowly,’ it can say, ‘Okay, let's skip the next two modules and see how you go.’ If that's suddenly too difficult, you can take a step back.
You can guide your own tutor.
“I think that's fundamentally different from a static curriculum. That's why we have these two elements working together: the dynamic curriculum and the conversation.”
The limits of AI language support
Eevi is currently using Gemini as its voice model across around 14 languages, including Japanese, Indonesian, and Chinese. Gemini’s recent update will expand this to around 35 languages. But relying on foundation models also determines which languages and dialects Eevi can support. Asked how Eevi deals with accents, dialects, and pronunciation, Schöffer said:
“Different LLMs support different dialects, and that's actually raised a much bigger issue for us.”
He sees an element of neo-colonialism in LLM development: major models are predominantly Western-developed, and those models effectively determine which dialects are represented and supported.
“We've already had users saying, ‘My mother speaks this dialect, and I want to learn it,’ but the model doesn't support it.”
The company is exploring whether the technology built for Eevi could also support dialects and endangered languages.
Schöffer sees that as potentially a separate product built on the same underlying technology. Generative AI can also make mistakes with vocabulary and grammar, which Schöffer admits is one reason Eevi currently can't offer some more niche languages.
An LLM might technically support a language without having sufficient contextual understanding, increasing the likelihood of errors. But he added:
“We don't want to remain permanently dependent on the major LLM providers, particularly as a European company.”
The longer-term aim is to build its own model with greater nuance around niche and protected languages and use that knowledge to teach them.
“But first we need to demonstrate commercial success in mainstream language learning.”
Building differently the second time around
As a second-time founder, Schöffer says building a company in the age of AI feels different.
“Normally, I'd say I know who to hire and how to approach certain problems, but I'm not sure I do anymore.”
He says that experience has given him a better understanding of what matters now and what can wait.
“When we started Hubs, I worked 60-plus-hour weeks, year after year. Looking back, half of those hours were probably spent on things that weren't particularly important. When you don't know what to do, sometimes you just put your head down and work harder.”
He has young children now and is approaching Eevi differently.
“I know the product needs to be right, and we're deliberately not doing everything as quickly as possible. In the past, I would have launched fast, pushed fast, and started advertising fast.”
Starting with international professionals
Eevi’s first target audience, which was also validated during the beta, is migrants or, more broadly, international professionals.
“We're a B2C app, so anyone can use Eevi, but initially we want to start small and focus on international professionals who want to progress beyond something like Duolingo but don't want to attend a traditional language school because of the price or lack of flexibility.
We're positioning ourselves somewhere in the middle.”
The suggested package is a six-month course at €49, while monthly pricing is €18.
The company says six months of Eevi costs roughly the same as one hour with a human tutor, depending on the tutor. The company also plans to experiment with B2B corporate sales.
“I know the Amsterdam startup and scaleup ecosystem very well, so we'll approach companies and ask whether they'd be interested in buying, say, 50 seats for international employees who want to learn Dutch.
“That's something we'll start exploring.”
Where Eevi sees the competition
Schöffer divides the competitive landscape into three groups: established language-learning apps, foundation-model providers, and AI-native language-learning startups. On established players such as Duolingo, he said:
“I'm not too concerned about them because they're so heavily invested in their existing models. That's the classic innovator's dilemma. Of course, you never know, but I don't necessarily see them taking the lead in this approach.” At the other extreme are the LLM providers themselves.
Could Gemini or OpenAI build language-learning layers directly on top of their models?
“I'd be surprised,” he said. “They're effectively in the token business, and I don't necessarily see why they would build every vertical application themselves.”
Between the two are companies like Eevi building dedicated AI-native language-learning products.
“I've seen more of those in the US than in Europe so far,” Schöffer shared.
Why Eevi raised after a year of bootstrapping
The founders bootstrapped Eevi for almost 12 months and, according to Schöffer, could have continued using their own money. But in a market moving this quickly, he believes speed matters more than dilution.
“And the right investors bring things personal capital does not: they pressure-test your thinking, open their network for the hires ahead, and hold you accountable."
Rockstart backed us at 3D Hubs before anyone else did. Having them do it again is worth more than just the check.”
According to Max ter Horst, Managing Partner of Rockstart, as AI reshapes education and work, conversational skills in foreign languages will become even more critical to economic mobility, inclusion, and global collaboration.
“Eevi is building a new kind of language learning experience centred around conversation, confidence, and accessibility.
We’re thrilled to back this exceptional team, which includes a founder with whom we’ve successfully partnered before.”
Schöffer acknowledges that his previous experience gives him an advantage when fundraising.
“I'm in a fortunate position because I already know a lot of VCs and they'll respond to me.
But with the way AI is developing, I've found that a lot of VCs are hesitant about two things: software in general and B2C.
If you say you're building a B2C language-learning product, the door can close pretty quickly.
VCs tend to work from certain checklists, and I've heard ‘come back when you have €1 million in revenue’ quite a lot. My reaction is: if I've already reached €1 million in revenue, I hope we're doing pretty well!”
The funding will support Eevi's public launch and scaling over the next 12 months.
Schöffer wants the company to demonstrate that AI can enable a fundamentally different approach to learning.
“I want people to recognise that learning — and in our case, language learning — can be significantly better.
There are hundreds of millions of people trying to learn a second language, and only a small proportion will ultimately succeed. That's an enormous waste of human energy.
The platform is new, and it’s still evolving, but I hope people use it and see the potential for a different way of learning.”
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