IT-Enterprise Experts Explain Where Industrial AI Starts at Hack&Match for Mechanical Engineering
At the first Hack&Match brokerage event dedicated to automation and digitalization in mechanical engineering, Oleksandr Ochkasov, AI Expert at IT-Enterprise, presented a practical approach to implementing artificial intelligence in industrial operations. Organized by EDIH Kyiv HiTech* in cooperation with APPAU and the Ukrainian Cluster Alliance, the event brought together more than 40 representatives of mechanical engineering companies, engineering firms, and system integrators.
One of the key challenges facing the market today is the “we want AI” mindset, which starts with the technology itself rather than a real production problem. In industry, however, AI is not a standalone “magic” chatbot. It is a layer built on top of reliable, high-quality production data.
“Industrial AI only works when there is solid data to build on: equipment data, maintenance and failure histories, operating hours, inspection results, technical documentation, downtime records, and quality data. If information is incomplete or scattered across different systems, AI will not fix the problem — it will simply replicate poor-quality data faster. The principle is simple: garbage in, garbage out,” said Oleksandr Ochkasov, AI Expert at IT-Enterprise.
He added that, according to McKinsey, 70% of companies seeking to realize value from AI encounter challenges related to data quality, integration, and accessibility. In manufacturing, this barrier is even more pronounced: surveys show that 46% of operations leaders identify the gap between IT and OT systems as the main obstacle to AI adoption.
That is why an integrated digital environment — combining EAM, MES, ERP, IIoT, and mobile tools for collecting primary data — is the foundation of an effective industrial AI framework. Using the IT-Enterprise ecosystem as an example, Oleksandr Ochkasov demonstrated an end-to-end approach to building a practical AI framework:
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On-site data collection: Smart EAM Mobile solutions capture the actual condition of equipment, inspection results, and defects.
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Operational analysis: AI EAM processes maintenance histories and equipment operating hours.
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Technical documentation: TechLink AI enables intelligent search and supports engineering decisions based on technical standards and drawings.
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Predictive maintenance: Predictive Maintenance algorithms identify anomalies and help prevent unplanned downtime. One of IT-Enterprise’s proprietary solutions in this area is Anna Maly.
Rather than showcasing yet another generative AI chatbot, IT-Enterprise focuses on taking a specific customer production scenario through to measurable business and financial results.
To ensure AI delivers tangible value, IT-Enterprise experts recommend following a structured implementation process:
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Identify a specific source of loss: equipment downtime, defects, repeat repairs, or loss of engineering knowledge.
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Collect and digitize data: establish automated or semi-automated collection of primary operational information.
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Launch a pilot: implement a focused use case on a single production line or piece of equipment.
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Measure results and scale: validate the business case and expand the solution across the wider operation.
Experts from IT-Enterprise and EDIH Kyiv HiTech are ready to help manufacturers assess their digital maturity, identify key sources of operational losses, and develop a roadmap for implementing an industrial AI framework. Companies can request an assessment and consultation by submitting an application through the EDIH Kyiv HiTech website.
The next in-person Hack&Match ecosystem meeting is scheduled for January 21, 2027, at Igor Sikorsky Kyiv Polytechnic Institute (KPI). The organizers are inviting manufacturers and system integrators to submit their own technology challenges and use cases.
IT-Enterprise continues to develop its AI ecosystem. As previously reported, the company’s AI technologies are used across various sectors of Ukraine’s economy, from logistics to defense.
According to the AI Focus 2026 study conducted by visual communications agency Top Lead, IT-Enterprise was placed in the highest category of companies undergoing AI transformation: “Advanced Stage of AI Adoption.” Analysts found that only 38.9% of Ukrainian companies had reached this level of digitalization. These companies are predominantly large enterprises, many of which are building their AI transformation on solutions developed by IT-Enterprise.
EDIH Kyiv HiTech is co-funded by the European Union. The views and opinions expressed are those of the author(s) only and do not necessarily reflect those of the European Union or the European Health and Digital Executive Agency (HaDEA). Neither the European Union nor the granting authority can be held responsible for them.
IT-Enterprise is a Ukrainian product-based IT company with more than 35 years of experience, supporting the digital transformation of some of the country’s largest companies in the real economy. Its clients include Interpipe, Ferrexpo, Nibulon, DTEK, Ukroboronprom, Ukrposhta, Ukrnafta, Ukrzaliznytsia, and others.
Since the first days of Russia’s full-scale invasion of Ukraine, the IT-Enterprise team has worked closely with government authorities on critical national projects, including humanitarian aid tracking, restoring procurement processes, and business relocation.
The company’s co-founder and CEO, Oleh Shcherbatenko, is a strong advocate of Industry 4.0 and Industry 5.0 approaches and technologies. IT-Enterprise develops its technological expertise through partnerships with Microsoft Azure, Oracle, Qlik, and Google.
IT-Enterprise has been developing its AI infrastructure since 2014 and has delivered more than 40 Industrial AI implementation projects. Its portfolio includes more than 1,450 completed projects across MilTech, agriculture, energy, retail, manufacturing, and financial and banking institutions.