“AI hype is intellectual laziness,” says Attila Moln\u00e1r, CEO of Lillyneir. The company he leads has become a defining systems engineering player in the Central European intelligent transport infrastructure sector. Its multidisciplinary team of more than 30 specialists competes in a field dominated by multinational giants, where current engineering know-how matters more than algorithms alone. AI does play a role in their work. The key question is where AI belongs and how it should be used. Lillyneir’s answer differs sharply from current market fashion.<\/p>\n
Lillyneir Ltd. was founded in 2011 in T\u00f6r\u00f6kb\u00e1lint, on the western edge of Budapest, originally focused on security technology. The strategic turning point came in 2017, when Attila Moln\u00e1r joined as owner and repositioned the company from a traditional systems integrator into a systems engineering provider. Commercial momentum followed. Over the next eight years, revenue grew by two orders of magnitude, roughly a hundredfold.<\/p>\n
Lillyneir develops six interconnected technology pillars: V2X communication systems, AI-powered traffic management, automated enforcement, advanced infrastructure monitoring, autonomous-ready intelligent transport infrastructure, and digital twin environments. Each pillar addresses a concrete operational problem in modern transport infrastructure.<\/p>\n
Two live deployments show the approach in practice. A structural monitoring system on the Tomori P\u00e1l Bridge in Hungary measures vibrations, dynamic loads, and structural changes in real time, then flags maintenance intervention points from the processed data before visible damage develops. On Road 451 near Orosh\u00e1za in southeastern Hungary, a certified high-speed weigh-in-motion system measures axle loads of heavy goods vehicles in free-flow traffic with legal-grade accuracy, protecting the pavement, the structure, and other road users.<\/p>\n
“We are not bridge engineers, but we have to understand how bridge engineers think. We are not tunnel builders either, but we have to understand the operational challenges of running a tunnel. And all of that has to be translated into the language of IT, electronics, and control engineering,”<\/em> Attila Moln\u00e1r explains.<\/p>\n That translation capability is the company’s competitive edge. Lillyneir does not deliver off-the-shelf solutions. Every project starts with a deep analysis of the specific infrastructure problem and produces a tailored engineering answer. The delivery model assigns the most qualified team to each task, drawing primarily on internal competence and bringing in external specialists when the problem demands it.<\/p>\n A second pillar of the model is vendor independence backed by a global supplier network. Lillyneir tracks the most advanced technology solutions from Australia through China to the United States, and often maintains direct working relationships with the local implementation partners executing on the ground. For the client, this means the engineering answer is never constrained by a single manufacturer’s catalogue.<\/p>\n Attila Moln\u00e1r’s AI critique targets one specific habit: treating AI as the default answer to every engineering problem. The technology itself has clear and legitimate uses in Lillyneir’s portfolio.<\/p>\n Large language models (LLMs) help with certain routine tasks. For control work operating on millisecond decision windows, LLMs do not qualify: their response time cannot be guaranteed, their outputs are non-deterministic, and their error profiles cannot be audited against road safety standards.<\/p>\n “We cannot hand control procedures over to a technology whose runtime we cannot guarantee and whose output is not yet reliably what we need it to be,”<\/em> Attila Moln\u00e1r says.<\/p>\n This distinction shapes Lillyneir’s AI strategy. The company applies machine learning where the intended purpose and mode of use justify it. Elsewhere, classical deterministic engineering methods do the work, particularly when safety considerations rule out probabilistic systems.<\/p>\n Lillyneir’s long-term strategic direction follows two reinforcing tracks. Predictive infrastructure management built on real-time data sits at the core of the first, enabling significant cost savings for state and municipal infrastructure owners on maintenance. Beyond that sits infrastructure-side support for Cooperative, Connected and Automated Mobility (CCAM). Safe operation of autonomous vehicles depends on high-reliability digital maps, standardised V2X communication, and real-time traffic management. While the automotive industry builds the vehicles, Lillyneir builds the road network intelligence on which those vehicles can operate safely.<\/p>\n As a sponsor of the 2026 Transport Research Arena conference in Budapest, Lillyneir signals a clear intent. The company is stepping onto the international R&D stage and converting its existing academic collaborations into durable, long-term research and development relationships. These include its partnership with the Budapest University of Technology and Economics (BME) and ongoing university partnerships in the Middle East.<\/p>","protected":false},"excerpt":{"rendered":" Lillyneir builds the engineering foundation for intelligent transport infrastructure, where AI serves engineering, not the other way around.<\/p>","protected":false},"author":4,"featured_media":2223,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_seopress_robots_primary_cat":"none","_seopress_titles_title":"AI hype is intellectual laziness - Interview with our CTO","_seopress_titles_desc":"Lillyneir builds the engineering foundation for intelligent transport infrastructure, where AI serves engineering, not the other way around.","_seopress_robots_index":"","footnotes":""},"categories":[8],"tags":[],"class_list":["post-2208","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-blog-article"],"_links":{"self":[{"href":"https:\/\/lillyneir.com\/ar\/wp-json\/wp\/v2\/posts\/2208","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/lillyneir.com\/ar\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/lillyneir.com\/ar\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/lillyneir.com\/ar\/wp-json\/wp\/v2\/users\/4"}],"replies":[{"embeddable":true,"href":"https:\/\/lillyneir.com\/ar\/wp-json\/wp\/v2\/comments?post=2208"}],"version-history":[{"count":2,"href":"https:\/\/lillyneir.com\/ar\/wp-json\/wp\/v2\/posts\/2208\/revisions"}],"predecessor-version":[{"id":2212,"href":"https:\/\/lillyneir.com\/ar\/wp-json\/wp\/v2\/posts\/2208\/revisions\/2212"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/lillyneir.com\/ar\/wp-json\/wp\/v2\/media\/2223"}],"wp:attachment":[{"href":"https:\/\/lillyneir.com\/ar\/wp-json\/wp\/v2\/media?parent=2208"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/lillyneir.com\/ar\/wp-json\/wp\/v2\/categories?post=2208"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/lillyneir.com\/ar\/wp-json\/wp\/v2\/tags?post=2208"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}The road ahead<\/h2>\n