The Vietnamese Experiment: AI Wrapped in Mini-Apps

The Vietnamese company Icetea AI & Robotics (IAI) has come up with a platform called Digesty, which takes a different approach to the problem than the big players. Instead of a universal chat interface where users have to come up with complex prompts themselves, it breaks AI down into specialized "mini-apps" — each one does exactly one thing and does it well. The user doesn't need to know how to "prompt." They simply choose what they want — write a Facebook post, summarize an article, plan a week's worth of content — enter the basic details, and the system returns a finished result in the right format. The writing style is automatically adapted to Vietnamese taste, not a universal Anglo-Saxon template. "If we see AI as a universal tool, many ordinary users actually only need a few simple but effective functions," explains Phuong Yen Tran, representative of the Digesty project, for VietNamNet. "Our goal is for people to be able to use AI immediately, instead of first having to learn how to communicate with it." The platform also draws data from Vietnamese news sources, reducing the risk of hallucinations and irrelevant answers that plague global chatbots when they try to respond to locally specific queries.

Why Translation Isn't Enough — Culture as a Hidden Barrier

The problem with global AI models isn't just the language itself. It's the cultural context. When a Czech sole trader asks ChatGPT for a Facebook ad text, the model generates grammatically correct Czech, but it lacks an understanding of Czech humor, shopping habits, or what actually works on a Czech customer. The same experience is described by Ms. Mai, an online seller from Hanoi: "I tried using AI to write advertising copy, but the result was either too robotic or didn't match the Vietnamese sales style. In the end, the edits cost me more time than if I had written it myself." This isn't a failure of the model — it's a failure of design. Models like GPT-5.5 or Claude Opus 4.8 work passably in Czech, but their training data is disproportionately English. It is estimated that over 50% of training data for large language models comes from English sources, while Czech accounts for a fraction of a percent.

Global Parallels: India as a Localization Laboratory

Vietnam is not the only country trying to adapt AI to its own needs. India has become one of the most interesting laboratories of AI localization in recent months. The startup Sarvam AI is developing models trained primarily on Indian languages — Hindi, Tamil, Telugu, and others. Their approach is different from Digesty's: instead of wrapping existing models, they are building their own language models from scratch, with an emphasis on Indian realities, names, places, and cultural references. And it's not just startups. Microsoft, Google, and Meta are investing in Indian AI infrastructure and the localization of their assistants. The reason is pragmatic: India has over 1.4 billion people, and only a minority speak English. Anyone who can't serve users in their native language won't succeed in the Indian market.

Europe and Czech: Where Are We Now?

For the Czech reader, the key question is: how well do AI tools handle Czech today? The answer is mixed. GPT-5.5 (OpenAI) and Claude Opus 4.8 (Anthropic) handle Czech at a very decent level — translations, text summarization, and basic copywriting work without major issues. Gemini from Google also doesn't do badly in Czech, especially thanks to Google's long-standing investments in the Czech language ecosystem (Translate, Czech search results). But when it comes to more specialized tasks — legal texts, marketing copywriting with an understanding of Czech culture, generating social media content that wouldn't seem "weird" to a Czech audience — the models still fall short. The European Union is responding to the problem with the ALT-EDIC (Alliance for Language Technologies) initiative, which aims to build European infrastructure for language technologies across all 24 official EU languages. In the Czech Republic, the Czech AI Factory in Ostrava project recently launched, intended to be a node in the European network for developing and testing AI models with an emphasis on the Central European language area.

What This Means for Czech Businesses and Users

The current situation yields several concrete recommendations: For everyday users: For daily tasks in Czech (text summarization, translation, explaining concepts), GPT-5.5 and Claude are more than sufficient. However, if you need creative or marketing text that truly needs to work in Czech, expect that you'll have to edit the output. For businesses: The "Vietnamese-style" approach — wrapping a large model in narrowly specialized applications with pre-prepared templates and local data — is a path that Czech companies should also consider. Building your own model is expensive, but fine-tuning an existing model on Czech data and wrapping it in a user-friendly interface is a realistic and relatively affordable project. For developers and startups: AI localization is one of the biggest untapped opportunities on the Czech market. While American companies compete for every percentage point in benchmarks, no one is properly addressing the need for AI to truly understand the Czech context — from official forms to specific humor. Whoever does this first and does it well will have a head start.

The Race for the Last Mile

The trend is clear. While the big labs in Silicon Valley race to build the smartest model in the world, the real adoption of AI is decided on the "last mile" — at the moment when a person in Vietnam, India, or the Czech Republic opens an app and finds out whether it actually understands them. The Digesty approach — breaking AI into small, specific tools that do one thing and do it in the local context — shows a direction that many local players could take. And it's not just about small markets. Even in Europe, it's becoming clear that one universal English AI won't be enough. For Czech readers, the simple message is this: AI tools in Czech are improving rapidly, but we won't achieve full linguistic and cultural parity with English for a long time. Those who want to use AI to its full potential today should know English — or wait until someone builds a Czech alternative.