{"id":29883,"date":"2026-01-22T17:01:18","date_gmt":"2026-01-22T17:01:18","guid":{"rendered":"https:\/\/nekudos.com\/sap-verisi-llm-besleme\/"},"modified":"2026-01-22T17:01:35","modified_gmt":"2026-01-22T17:01:35","slug":"sap-verisi-llm-besleme","status":"publish","type":"post","link":"https:\/\/nekudos.com\/en\/sap-verisi-llm-besleme\/","title":{"rendered":"SAP Verisi ile LLM Entegrasyonu ve Grounding Yaklasimi"},"content":{"rendered":"

SAP Verisi ile LLM Nas\u0131l Beslenir<\/strong><\/h1>\n
\n

Giri\u015f<\/strong><\/h3>\n

SAP verisi ile LLM (Large Language Model) besleme, kurumsal yapay zekan\u0131n en g\u00fc\u00e7l\u00fc uygulama alanlar\u0131ndan biridir. sap llm integration, i\u015fletmelerin sahip oldu\u011fu b\u00fcy\u00fck ve yap\u0131land\u0131r\u0131lm\u0131\u015f SAP verisini do\u011fal dil modelleriyle anlamland\u0131rmas\u0131n\u0131 sa\u011flar. B\u00f6ylece yapay zek\u00e2, yaln\u0131zca genel bilgiyle de\u011fil, kuruma \u00f6zg\u00fc verilerle de \u201cgrounded\u201d hale gelir. Bu durum, karar destek sistemlerinden otomasyona kadar geni\u015f bir etki yarat\u0131r.<\/p>\n

\n

SAP Verisi ile LLM Nas\u0131l Beslenir tan\u0131m\u0131<\/strong><\/h3>\n

SAP verisiyle LLM besleme, kurumsal ERP ve BTP ortamlar\u0131ndaki verilerin LLM modellerine ba\u011flanarak s\u00fcre\u00e7 \u00e7\u0131kar\u0131m\u0131, do\u011fal dil sorgulama ve otomatik yan\u0131t \u00fcretimi i\u00e7in kullan\u0131lmas\u0131n\u0131 ifade eder. sap llm integration, \u00f6zellikle grounding yakla\u015f\u0131m\u0131yla LLM\u2019in kurumsal ba\u011flam i\u00e7inde daha do\u011fru ve anlaml\u0131 sonu\u00e7lar \u00fcretmesini m\u00fcmk\u00fcn k\u0131lar. Bu s\u00fcre\u00e7, verinin \u00e7ekilmesi, normalize edilmesi ve API katman\u0131 \u00fczerinden LLM\u2019e aktar\u0131lmas\u0131 ad\u0131mlar\u0131n\u0131 i\u00e7erir.<\/p>\n

\n

sap llm integration nas\u0131l \u00e7al\u0131\u015f\u0131r<\/strong><\/h3>\n

SAP ortam\u0131 ile LLM entegrasyonu, veri servisleri, API gateway\u2019ler ve g\u00fcvenli ba\u011flant\u0131lar \u00fczerinden sa\u011flan\u0131r. SAP BTP (Business Technology Platform) burada merkezi bir rol oynar. BTP \u00fczerindeki AI Core ve AI Launchpad servisleri, verinin modelle etkile\u015fiminde hem g\u00fcvenli\u011fi hem de performans\u0131 y\u00f6netir.<\/p>\n

Temel parametreler ve ayarlar<\/strong><\/h4>\n

Entegrasyonda belirlenmesi gereken temel parametreler \u015funlard\u0131r: <\/p>\n

    \n
  • Veri kapsam\u0131:<\/strong> Hangi SAP tablolar\u0131 veya mod\u00fcllerinin kullan\u0131laca\u011f\u0131. <\/li>\n
  • Grounding derinli\u011fi:<\/strong> LLM\u2019in kurumsal ba\u011flama ne kadar ba\u011fl\u0131 \u00e7al\u0131\u015faca\u011f\u0131. <\/li>\n
  • Model parametreleri:<\/strong> Token penceresi, ba\u011flam uzunlu\u011fu, yan\u0131t yo\u011funlu\u011fu gibi ayarlar. <\/li>\n
  • Ba\u011flant\u0131 g\u00fcvenli\u011fi:<\/strong> OAuth, SAML veya API Key do\u011frulama y\u00f6ntemleri.<\/li>\n<\/ul>\n

    S\u0131k yap\u0131lan hatalar ve ka\u00e7\u0131nma y\u00f6ntemleri<\/strong><\/h4>\n
      \n
    • Veri anonimle\u015ftirme yap\u0131lmadan model e\u011fitmek, g\u00fcvenlik riski do\u011furur. <\/li>\n
    • SAP mod\u00fclleri aras\u0131 veri tutars\u0131zl\u0131klar\u0131 LLM sonu\u00e7 do\u011frulu\u011funu d\u00fc\u015f\u00fcr\u00fcr. <\/li>\n
    • A\u015f\u0131r\u0131 geni\u015f veri seti, model performans\u0131n\u0131 yava\u015flatabilir.
      \nBu hatalardan ka\u00e7\u0131nmak i\u00e7in veri haz\u0131rl\u0131k s\u00fcrecinde veri kalitesinin ve g\u00fcvenli\u011finin \u00f6nceliklendirilmesi gerekir.<\/li>\n<\/ul>\n

      Ger\u00e7ek sistemlerde uygulama \u00f6rnekleri<\/strong><\/h4>\n

      Bir finans mod\u00fcl\u00fcnden al\u0131nan sat\u0131\u015f tahmin verisinin LLM\u2019e aktar\u0131lmas\u0131yla model, do\u011fal dil \u00fczerinden \u201c\u00f6n\u00fcm\u00fczdeki \u00e7eyrekte hangi b\u00f6lge d\u00fc\u015f\u00fck performans g\u00f6sterebilir?\u201d gibi sorulara analitik yan\u0131t \u00fcretebilir. SAP BTP \u00fczerinde bu yap\u0131, AI Core ve SAP Datasphere \u00fczerinden ger\u00e7ekle\u015ftirilebilir.<\/p>\n

      \n

      Teknik a\u00e7\u0131klama (derin seviye)<\/strong><\/h3>\n

      sap llm integration s\u00fcreci \u00fc\u00e7 katmandan olu\u015fur: <\/p>\n

        \n
      1. Veri katman\u0131:<\/strong> SAP ERP, S\/4HANA veya SuccessFactors gibi kaynaklardan veri al\u0131n\u0131r. <\/li>\n
      2. K\u00f6pr\u00fc katman\u0131:<\/strong> NeKu.AI ya da SAP BTP\u2019nin API Management bile\u015feni, veriyi LLM\u2019e uygun formata d\u00f6n\u00fc\u015ft\u00fcr\u00fcr. <\/li>\n
      3. Model katman\u0131:<\/strong> LLM, grounding teknikleriyle kurumsal veri da\u011farc\u0131\u011f\u0131na ba\u011flan\u0131r.<\/li>\n<\/ol>\n

        Veri ak\u0131\u015f\u0131 genellikle REST veya GraphQL API\u2019leri \u00fczerinden ger\u00e7ekle\u015fir. LLM, sorgu geldi\u011finde grounding katman\u0131 \u00fczerinden en g\u00fcncel SAP verisine eri\u015ferek yan\u0131t olu\u015fturur. Bu yap\u0131, hem \u00f6zetleme hem de karar destek \u00e7\u0131kt\u0131lar\u0131nda g\u00fcvenilirli\u011fi art\u0131r\u0131r. \u00d6zellikle SAP AI Core kullan\u0131ld\u0131\u011f\u0131nda model s\u00fcr\u00fcmleri y\u00f6netilebilir hale gelir.<\/p>\n

        \n

        \u0130\u015fletmeler i\u00e7in neden kritiktir<\/strong><\/h3>\n
          \n
        • Performans:<\/strong> Ger\u00e7ek zamanl\u0131 veriyle \u00e7al\u0131\u015fan LLM, tahmin do\u011frulu\u011funu art\u0131r\u0131r. <\/li>\n
        • G\u00fcvenilirlik:<\/strong> Sonu\u00e7lar, kurumsal SAP verisine dayan\u0131r. <\/li>\n
        • Maliyet:<\/strong> Bilgiye eri\u015fimde otomasyon, dan\u0131\u015fmanl\u0131k ve analiz maliyetini d\u00fc\u015f\u00fcr\u00fcr. <\/li>\n
        • \u00d6l\u00e7ekleme:<\/strong> SAP BTP\u2019nin bulut altyap\u0131s\u0131 ile entegrasyon, esnek kaynak y\u00f6netimi sa\u011flar. <\/li>\n
        • Otomasyon:<\/strong> Model \u00e7\u0131kt\u0131lar\u0131 Robotic Process Automation (RPA) sistemlerine aktar\u0131labilir. <\/li>\n
        • Karar alma:<\/strong> Y\u00f6netim seviyesinde veri destekli \u00f6ng\u00f6r\u00fcler \u00fcretilebilir. <\/li>\n
        • Operasyonel verimlilik:<\/strong> LLM, i\u015f ak\u0131\u015flar\u0131n\u0131 h\u0131zland\u0131r\u0131r ve kullan\u0131c\u0131 etkile\u015fimlerini sadele\u015ftirir.<\/li>\n<\/ul>\n
          \n

          Bu kavram NeKuDos Teknoloji i\u00e7inde nas\u0131l uygulan\u0131r<\/strong><\/h3>\n

          NeKuDos Teknoloji, SAP dan\u0131\u015fmanl\u0131\u011f\u0131 ve entegrasyon deneyimini NeKu.AI platformuyla birle\u015ftirerek LLM tabanl\u0131 grounding \u00e7\u00f6z\u00fcmlerine odaklan\u0131r. SAP BTP \u00fczerindeki AI Core, Event Mesh ve Integration Suite bile\u015fenleri kullan\u0131larak LLM modelleri kurumsal veri ile senkronize edilir.
          \nBu yakla\u015f\u0131mda LLM, statik bir model olarak de\u011fil, s\u00fcrekli \u00f6\u011frenen bir sistem olarak \u00e7al\u0131\u015f\u0131r. B\u00f6ylece SAP s\u00fcre\u00e7lerinden elde edilen operasyonel sinyaller, LLM taraf\u0131ndan yorumlanabilir hale gelir.<\/p>\n

          \n

          SAP dan\u0131\u015fmanlar\u0131, IT y\u00f6neticileri, CTOlar i\u00e7in ger\u00e7ek bir senaryo<\/strong><\/h3>\n
            \n
          1. Sorun:<\/strong> Bir \u00fcretim firmas\u0131, tedarik zinciri verilerini analiz ederken manuel raporlama s\u00fcrecinde zaman kayb\u0131 ya\u015famaktad\u0131r. <\/li>\n
          2. Ba\u011flam:<\/strong> SAP S\/4HANA \u00fczerinden tedarik zinciri verileri tutulmakta, fakat analizler birden fazla sistem aras\u0131nda da\u011f\u0131n\u0131k durumdad\u0131r. <\/li>\n
          3. Kavram\u0131n uygulanmas\u0131:<\/strong> sap llm integration s\u00fcreciyle SAP Datasphere verileri NeKu.AI \u00fczerindeki LLM modeline ba\u011flan\u0131r. Model grounding katman\u0131 sayesinde tedarik zinciri g\u00f6stergelerini anl\u0131k sorgular. <\/li>\n
          4. Sonu\u00e7:<\/strong> LLM, do\u011fal dilde \u201changi tedarik\u00e7i en y\u00fcksek gecikme oran\u0131na sahip?\u201d sorusuna SAP verisini kullanarak yan\u0131t \u00fcretir. <\/li>\n
          5. \u0130\u015f etkisi:<\/strong> Raporlama s\u00fcresi %60 azal\u0131r, karar d\u00f6ng\u00fcleri h\u0131zlan\u0131r.<\/li>\n<\/ol>\n
            \n

            S\u0131k yap\u0131lan hatalar ve en iyi uygulamalar<\/strong><\/h3>\n

            Yayg\u0131n hatalar:<\/strong> <\/p>\n

              \n
            • LLM\u2019e ba\u011flams\u0131z veri sa\u011flamak. <\/li>\n
            • SAP API katman\u0131n\u0131 do\u011frudan a\u00e7\u0131\u011fa \u00e7\u0131karmak. <\/li>\n
            • Grounding ad\u0131m\u0131n\u0131 atlayarak modelin hatal\u0131 tahminler \u00fcretmesine neden olmak.<\/li>\n<\/ul>\n

              En iyi uygulamalar:<\/strong> <\/p>\n

                \n
              • SAP verisini \u00f6nce normalize etmek, sonra embedding katman\u0131na aktarmak. <\/li>\n
              • LLM sorgular\u0131n\u0131 izleyip model yan\u0131tlar\u0131n\u0131 d\u00fczenli olarak do\u011frulamak. <\/li>\n
              • BTP AI Core \u00fczerinde s\u00fcr\u00fcm kontrol\u00fc yapmak. <\/li>\n
              • G\u00fcvenli API ba\u011flant\u0131lar\u0131 ve eri\u015fim y\u00f6netimi sa\u011flamak.<\/li>\n<\/ul>\n
                \n

                Sonu\u00e7<\/strong><\/h3>\n

                SAP verisi ile LLM besleme, kurumsal AI d\u00f6n\u00fc\u015f\u00fcm\u00fcn\u00fcn teknik belkemi\u011fini olu\u015fturur. sap llm integration yakla\u015f\u0131m\u0131 sayesinde i\u015fletmeler, yaln\u0131zca bilgiye eri\u015fen de\u011fil, bilgiyi kurum k\u00fclt\u00fcr\u00fcne uygun bi\u00e7imde yorumlayan sistemlere sahip olur. Grounding, SAP AI ve BTP altyap\u0131lar\u0131n\u0131n birle\u015fimiyle do\u011fru veri, do\u011fru model, do\u011fru sonu\u00e7 dengesini sa\u011flar.
                \nNeKuDos Teknoloji\u2019nin AI ve entegrasyon uzmanl\u0131\u011f\u0131, bu d\u00f6n\u00fc\u015f\u00fcm\u00fc teknik do\u011fruluk ve g\u00fcvenilir mimari ile ger\u00e7e\u011fe d\u00f6n\u00fc\u015ft\u00fcrmektedir.<\/p>","protected":false},"excerpt":{"rendered":"

                SAP Verisi ile LLM Nas\u0131l Beslenir Giri\u015f SAP verisi ile LLM (Large Language Model) besleme, kurumsal yapay zekan\u0131n en g\u00fc\u00e7l\u00fc uygulama alanlar\u0131ndan biridir. sap llm integration, i\u015fletmelerin sahip oldu\u011fu b\u00fcy\u00fck ve yap\u0131land\u0131r\u0131lm\u0131\u015f SAP verisini do\u011fal dil modelleriyle anlamland\u0131rmas\u0131n\u0131 sa\u011flar. B\u00f6ylece yapay zek\u00e2, yaln\u0131zca genel bilgiyle de\u011fil, kuruma \u00f6zg\u00fc verilerle de \u201cgrounded\u201d hale gelir. Bu durum,…<\/p>","protected":false},"author":2,"featured_media":29884,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_sitemap_exclude":false,"_sitemap_priority":"","_sitemap_frequency":"","footnotes":""},"categories":[122],"tags":[],"class_list":["post-29883","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-sap","category-122","description-off"],"yoast_head":"\nSAP Verisi ile LLM Entegrasyonu ve Grounding Yaklasimi - NeKuDos Teknoloji<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/nekudos.com\/en\/sap-verisi-llm-besleme\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"SAP Verisi ile LLM Entegrasyonu ve Grounding Yaklasimi - NeKuDos Teknoloji\" \/>\n<meta property=\"og:description\" content=\"SAP Verisi ile LLM Nas\u0131l Beslenir Giri\u015f SAP verisi ile LLM (Large Language Model) besleme, kurumsal yapay zekan\u0131n en g\u00fc\u00e7l\u00fc uygulama alanlar\u0131ndan biridir. sap llm integration, i\u015fletmelerin sahip oldu\u011fu b\u00fcy\u00fck ve yap\u0131land\u0131r\u0131lm\u0131\u015f SAP verisini do\u011fal dil modelleriyle anlamland\u0131rmas\u0131n\u0131 sa\u011flar. B\u00f6ylece yapay zek\u00e2, yaln\u0131zca genel bilgiyle de\u011fil, kuruma \u00f6zg\u00fc verilerle de \u201cgrounded\u201d hale gelir. 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