LLM Architectural Pattern and Usecase in SAP

Integrating 𝗟𝗮𝗿𝗴𝗲 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲 𝗠𝗼𝗱𝗲𝗹𝘀 (𝗟𝗟𝗠𝘀) within 𝗦𝗔𝗣 𝗲𝗻𝘃𝗶𝗿𝗼𝗻𝗺𝗲𝗻𝘁𝘀 enhances business processes efficiency and effectiveness. Leveraging below common architectural patterns organizations can tailor LLMs for specific needs. 1️⃣ 𝗥𝗲𝘁𝗿𝗶𝗲𝘃𝗮𝗹-𝗔𝘂𝗴𝗺𝗲𝗻𝘁𝗲𝗱 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝗼𝗻 (𝗥𝗔𝗚), 2️⃣ 𝗙𝗶𝗻𝗲-𝗧𝘂𝗻𝗶𝗻𝗴 3️⃣ 𝗣𝗿𝗲-𝗧𝗿𝗮𝗶𝗻𝗶𝗻𝗴

🔖1️⃣𝗥𝗔𝗚 𝗨𝘀𝗲 𝗖𝗮𝘀𝗲𝘀 𝗶𝗻 𝗦𝗔𝗣

🎯𝗗𝘂𝗽𝗹𝗶𝗰𝗮𝘁𝗲 𝗜𝗻𝘃𝗼𝗶𝗰𝗲 𝗗𝗲𝘁𝗲𝗰𝘁𝗶𝗼𝗻 𝗶𝗻 𝗦𝗔𝗣 𝗘𝗥𝗣 𝗙𝗶𝗻𝗮𝗻𝗰𝗶𝗮𝗹𝘀: RAG can identifies potential duplicate invoices by comparing incoming invoices against a database, reducing financial discrepancies.

🎯𝗖𝘂𝘀𝘁𝗼𝗺𝗲𝗿 𝗜𝗻𝗾𝘂𝗶𝗿𝘆 𝗥𝗲𝘀𝗼𝗹𝘂𝘁𝗶𝗼𝗻 𝗶𝗻 𝗦𝗔𝗣 𝗦𝗮𝗹𝗲𝘀 𝗖𝗹𝗼𝘂𝗱: RAG can retrieves relevant information to generate comprehensive, personalized responses, boosting customer satisfaction.

🎯𝗖𝗼𝗺𝗽𝗹𝗶𝗮𝗻𝗰𝗲 𝗠𝗼𝗻𝗶𝘁𝗼𝗿𝗶𝗻𝗴 𝗶𝗻 𝗦𝗔𝗣 𝗚𝗥𝗖 : RAG can scans regulatory databases and documentation, alerting officers to potential issues and enhancing compliance.

🔖2️⃣𝗙𝗶𝗻𝗲-𝗧𝘂𝗻𝗶𝗻𝗴 𝗨𝘀𝗲 𝗖𝗮𝘀𝗲𝘀 𝗶𝗻 𝗦𝗔𝗣:

🎯𝗣𝗲𝗿𝘀𝗼𝗻𝗮𝗹𝗶𝘇𝗲𝗱 𝗠𝗮𝗿𝗸𝗲𝘁𝗶𝗻𝗴 𝗖𝗮𝗺𝗽𝗮𝗶𝗴𝗻𝘀 𝗶𝗻 𝗦𝗔𝗣 𝗠𝗮𝗿𝗸𝗲𝘁𝗶𝗻𝗴 𝗖𝗹𝗼𝘂𝗱: Fine-tuning LLMs on customer data enables highly personalized marketing content, increasing engagement.

🎯𝗛𝘂𝗺𝗮𝗻 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀 𝗧𝗮𝗹𝗲𝗻𝘁 𝗔𝗰𝗾𝘂𝗶𝘀𝗶𝘁𝗶𝗼𝗻 𝗶𝗻 𝗦𝗔𝗣 𝗦𝘂𝗰𝗰𝗲𝘀𝘀𝗙𝗮𝗰𝘁𝗼𝗿𝘀: Fine-tuning on job descriptions and hiring data automates candidate screening, improving recruitment efficiency.

🎯𝗙𝗶𝗻𝗮𝗻𝗰𝗶𝗮𝗹 𝗙𝗼𝗿𝗲𝗰𝗮𝘀𝘁𝗶𝗻𝗴 𝗶𝗻 𝗦𝗔𝗣 𝗦/𝟰𝗛𝗔𝗡𝗔 𝗙𝗶𝗻𝗮𝗻𝗰𝗲: Fine-tuned LLMs produce detailed financial forecasts, supporting strategic decisions.

🔖3️⃣𝗣𝗿𝗲-𝗧𝗿𝗮𝗶𝗻𝗶𝗻𝗴 𝗨𝘀𝗲 𝗖𝗮𝘀𝗲𝘀 𝗶𝗻 𝗦𝗔𝗣

🎯𝗘𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲 𝗞𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁 𝗶𝗻 𝗦𝗔𝗣 𝗘𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲 𝗣𝗼𝗿𝘁𝗮𝗹: Pre-trained LLMs assist employees in locating information, enhancing productivity.

🎯𝗢𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗘𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝗰𝘆 𝗶𝗻 𝗦𝗔𝗣 𝗘𝗥𝗣 (𝗘𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲 𝗣𝗹𝗮𝗻𝗻𝗶𝗻𝗴): Pre-trained LLMs analyze operational data to suggest optimizations, driving efficiency.

🎯𝗖𝘂𝘀𝘁𝗼𝗺𝗲𝗿 𝗦𝘂𝗽𝗽𝗼𝗿𝘁 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻 𝗶𝗻 𝗦𝗔𝗣 𝗦𝗲𝗿𝘃𝗶𝗰𝗲 𝗖𝗹𝗼𝘂𝗱: Pre-trained LLMs automate support inquiries, improving response times.

Implementing these LLM strategies streamlines processes and enhances decision-making, providing a competitive edge. For detailed use case scenarios or PoC demos, contact 𝗡𝗲𝘅𝗚𝗲𝗻𝗖𝗼𝗺𝗽𝗮𝗻𝘆.𝗮𝗶