{"id":987628556,"date":"2026-04-27T14:43:19","date_gmt":"2026-04-27T12:43:19","guid":{"rendered":"https:\/\/staging.omnys.com\/generative-ai\/"},"modified":"2026-09-10T13:54:33","modified_gmt":"2026-09-10T11:54:33","slug":"generative-ai","status":"publish","type":"page","link":"https:\/\/www.omnys.com\/en\/ict-cloud-services\/generative-ai\/","title":{"rendered":"Generative AI"},"content":{"rendered":"

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Generative AI<\/h1>\n

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We bring generative AI into business processes: RAG, AI agents and tailored assistants for every industry. We do not assemble components \u2014 we develop differentiating solutions grounded in scientific research and validated on real enterprise projects. <\/span><\/p>\n

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Our approach<\/span><\/h4>\n

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Applied research, not just integration<\/h2>\n

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Unlike system integrators that assemble APIs and components, the Omnys team brings applied research expertise that translates into levels of accuracy and reliability above the market average. Our proprietary LLM tuning pipelines adopt frontier techniques developed in-house and validated by internationally awarded scientific publications. <\/p>\n

We invest actively in R&D and share our results by engaging with the international community: from the Best Paper Award at IntelliSys 2025 in Amsterdam, to publications at IEEE WCCI and ESANN and our research on ML for Demand Forecasting with +69% accuracy. This approach allows us to bring concrete, effective solutions to market across different industries \u2014 from pharma to manufacturing, from media to automotive. <\/p>\n

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Best Paper Award \u00b7 IntelliSys 2025, Amsterdam<\/pee> <\/p>\n

Synthetic Data Generation for RAG<\/h3>\n

“Domain-Specific and Cross-Lingual Synthetic Data Generation for Information Retrieval Training in RAG Applications”<\/pee> <\/div>\n

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+69%<\/span> <\/div>\n

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Applied research<\/pee> <\/p>\n

ML for Demand Forecasting<\/h3>\n

Forecasting accuracy for efficient supply chains.<\/pee> <\/div>\n

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Scientific publications<\/pee> <\/p>\n

IEEE WCCI 2022 \u00b7 IntelliSys 2020 \u00b7 ESANN 2020<\/h3>\n

Information Retrieval, neural networks and optimization for industrial applications.<\/pee> <\/div>\n

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