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    <title>Legacy-Edo-Zalezhnist-En — TechCom</title>
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      <title>Maintaining continuity during phased legacy ERP system migrations</title>
      <link>https://techcom.org.ua/en/bpm-en/phased-legacy-erp-migration-for-uninterrupted-transformation/</link>
      <pubDate>Fri, 29 May 2026 23:18:39 +0300</pubDate>
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      <description>&lt;!-- wp:freeform --&gt;&#xA;&lt;p&gt;Legacy ERP systems in the public sector have become bottlenecks for development and adaptation to modern requirements. Any change, integration with new government services, or functional update takes 3–6 months and often requires downtime. This leads to departments creating their own &#34;shadow&#34; IT solutions to bypass limitations, and the launch of new electronic services or adaptation to legislative changes occurs significantly slower than among competitors.&lt;/p&gt;&lt;p&gt;As an integration solutions architect with 15 years of experience, I believe that instead of trying to revive a monolith or replace it with a single &#34;big bang,&#34; the path to successful digital transformation lies in phased decomposition of legacy ERP. This means extracting individual functions into microservices with API access, allowing for system modernization without business interruption and with minimal risks.&lt;/p&gt;</description>
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      <title>Deploying domain-specific AI models in enterprise environments</title>
      <link>https://techcom.org.ua/en/software-development/domain-specific-ai-models-for-enterprise-applications/</link>
      <pubDate>Mon, 23 Mar 2026 16:52:43 +0200</pubDate>
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      <description>&lt;!-- wp:freeform --&gt;&#xD;&#xA;&lt;p&gt;In 2026, the corporate environment is undergoing a significant transformation, where artificial intelligence is moving from experimental projects to the core of new solution architectures. The 2026-2027 horizon is defining, as large-scale AI integration into business processes is occurring now, demanding a shift from general models to highly specialized ones. According to Gartner, by 2028, over half of the GenAI models enterprises will use will be domain-specific, underscoring the relevance of this direction today. This trend is driven by the need for deeper automation of cognitive work and decision-making, as well as the necessity to manage AI risks beyond standard approaches.&lt;/p&gt;</description>
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