Artificial Intelligence Is Not Just a Chatbot. Industry Needs Intelligent Applications and Processes
Stratox Presents a Vision of AI That Transforms Internal Processes and Opens the Path to Efficiency and Speed.
Prague, May 5, 2025 – Discussions about the use of artificial intelligence in companies today often focus on well-known generative tools, assistants, or automation of routine tasks. As a result, companies invest in solutions that speed up certain processes but do not address the core of the business—where efficiency, costs, and the use of key resources are decided. In the context of industry and manufacturing, this creates a paradox: the technology is present, but its benefits remain limited. According to Eurostat data, only 8% of European manufacturing companies use artificial intelligence in their operations. The Czech company Stratox warns that implementing AI can accelerate production by tens of percent.
The true potential of artificial intelligence lies in its ability to intervene in complex internal processes and support smarter decision-making—based on data, context, and prediction of possible scenarios. So-called intelligent business logic represents a shift from mere automation to optimization and even transformation: to what truly brings speed to the company, saves energy, and creates space for more efficient investments. This concerns mainly production management, capacity utilization, logistics optimization, or energy consumption control—not just customer chats or measuring customer satisfaction in call centers.
This is exactly the area Czech company Stratox focuses on, helping manufacturing enterprises integrate so-called embedded AI—artificial intelligence embedded directly into the application layer of systems that influence company operations. “AI should not be an add-on but part of the logic by which the company operates. Instead of discussions about replacing a few jobs, we focus on how to use key company resources more efficiently and reduce operational costs—for example, by optimizing inventories, production flows, logistics, or more effective deployment of machinery. The goal is to create intelligent operational models that allow saving one large crane, one turbine, or an entire production hall and, for instance, produce a locomotive or a drone twice as fast with the same number of employees,” says Patrik Horný, Managing Partner of Stratox.
Breakthrough Potential for Czech Industry
Stratox believes that implementing intelligent business and operational models can represent a real breakthrough for Czech industry. By integrating AI solutions into their unique processes, manufacturing companies can achieve significant efficiency gains, cost reductions, and competitive advantages on the market.
“This approach focuses on strengthening what makes each company unique and on developing proprietary software solutions with integrated AI that precisely match specific needs and competitive advantages… Such investments in AI make real sense,”
explains Horný.
Introducing AI into key processes such as production, planning, or logistics leads to significant savings and higher flexibility. In the context of Czech industry, which faces pressure to improve efficiency and a shortage of qualified labor, this can be a decisive advantage. With proper implementation, companies can achieve substantial performance increases without having to restructure employment or make large investments in new capacities. According to Patrik Horný, embedding AI can increase manufacturing output by tens of percent.
What Companies Do Wrong—and How to Change It
According to Stratox, many companies make the mistake of applying AI in isolation without addressing the context of the entire business model, which must change simultaneously. They introduce tools that remain on the periphery of infrastructure or spend a long time testing models that never reach production. The result is fragmentation and lost potential.
Stratox therefore developed its own framework, CodeNOW AI Factory, which enables companies to design and operate so-called purpose-driven AI. “These are specific, purpose-built AI models that address concrete business needs with the most optimal AI technology. The platform allows creating scalable AI microservices that can be safely developed, trained, and efficiently deployed across multiple environments up to production, while also considering regulatory and security requirements,” explains Patrik Horný.
Companies that manage to harness AI’s potential at the very core of their operational logic gain an edge—not because of the technology itself, but because of their ability to transform it into a concrete and measurable advantage, into an intelligent business model.