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Introduction
During SAP Sapphire 2024, SAP announced plans to integrate generative AI across its business portfolio, enabling customers to use the potential of business AI. Since then, SAP has delivered more than 100 new generative AI use cases. The SAP AI Foundation is designed to support SAP's standard applications, processes, and data in a highly secure way that protects data privacy and meets enterprise-level standards. The same AI Foundation allows partners to build custom AI solutions while benefiting from all the experience, integration aspects, and technologies to build and integrate AI using both SAP and non-SAP data.
About the Hack2Build Initiative
The Hack2Build SAP Business AI edition was created to help focus partners develop business AI solutions that are relevant, reliable, and responsible. Partners used SAP AI Core along with SAP Business Technology Platform (SAP BTP) services, including SAP HANA Cloud Vector Engine's Retrieval Augmented Generation (RAG). These capabilities helped contextualize information with any of the available 23 Large Language Models (LLMs) to provide enterprise-grade responses. Partners also utilized existing business services such as Document Information Extraction and Data Attribute Recommendation to enhance their AI solutions.
The Hack2Build initiative ran from October 8-16, 2024, with 26 focus partners participating in a 7-day challenge to build working business AI prototypes. Each partner's use case was evaluated for technical feasibility and customer relevance. SAP experts provided guidance and coaching to partners with accepted use cases.
The event concluded with three demo jam sessions where partners showcased their working prototypes that integrated SAP BTP and SAP AI Core services with both SAP and non-SAP data. Each demo jam session produced a winner and two runners-up, resulting in nine winning solutions. This blog highlights the use cases developed by these winning partners.
Winning Solutions
Group1
The following partners from Asia Pacific Japan and Europe emerged as winners in the first demo jam session, presented in order of Winner, First Runner-up, and Second Runner-up.
LTIMindtree
The NaviCollect solution, built on SAP Business Technology Platform (SAP BTP) using SAP Business AI services, aims to transform the accounts receivable process for finance functions. The solution addresses challenges such as time-consuming customer risk evaluation, inefficient collection management, and inaccurate cash flows from customer collections. NaviCollect features AI-driven dynamic risk indicators, efficient collection processes, automation of manual tasks, and prediction and recommendation of actions. The solution leverages both narrow AI for forecasting cash flows and uses Generative AI for dynamic customer risk management. For credit risk analysis, external market data providers are ingested in SAP HANA Vector Engine to correlate customer credit risk evaluation over time. The solution benefits personas such as credit collection agents, finance managers, and treasurers by providing improved risk management, accuracy, and agility.
Infosys
Infosys EV Battery Management is a prototype that optimizes the battery recycling management process using AI. The current process is costly, inefficient, and lacks compliance. The solution uses SAP Business AI, Generative AI Hub, and GPT-4o model to analyze images of batteries and predict the type of battery, identify metal extraction process and predict the percentage of metals to be extracted to optimize the supply chain processes.The prototype aims to reduce carbon emissions, make the supply chain more robust, and meet demands on sourcing costly raw materials. The solution is built using Multimodal analysis of battery images to determine type and recycling process, Prediction of metal extraction percentage using SAP AI Core, Generative AI Hub GPT-4o model, SAP Build Process Automation for approval and shipping of batteries, Data Attribute Recommendation model , SAP Cloud Application Programming Model (CAP) framework for logic and UI development, and by using the capabilities of SAP HANA Vector Engine with LangChain integration to build the AI application.
Tech Mahindra
RecogX.AI solution addresses the end-to-end MRO process for medical equipment spare parts using Generative AI and image recognition. Using Multimodal inputs with GPT4o for Image Recognition on SAP AI Core, the solution identifies spare parts uploaded by a service technician during the service of the medical equipment. Once parts are identified, the parts information is retrieved using SAP HANA Vector Engine to access vendor-specific information, part specifications, equipment service history and warranty information.
The solution improves efficiency of maintenance process, productivity, and customer satisfaction by automating the identification of medical equipment spare parts and providing relevant information. The prototype is built as a SAP Fiori application on SAP BTP, Cloud Foundry environment.
Group2
The following partners from Americas and Europe emerged as winners in the second demo jam session, presented in order of Winner, First Runner-up, and Second Runner-up.
Numen
Smart Legal Lens is an AI-powered solution that transforms how enterprise legal teams analyze and manage contracts. Designed specifically for mergers and acquisitions (M&A), this tool processes complex legal documents at scale, uncovering potential risks and streamlining workflows to safeguard financial interests. The solution excels in identifying 13 critical risk categories in contracts that should be considered during the M&A due diligence process, including change of control clauses and intellectual property rights. Through advanced document processing, Smart Legal Lens automatically extracts and analyzes key information, such as contract parties and types, expiration dates, financial commitments, and high-risk clauses, along with their implications.
Built on SAP BTP and powered by Mistral's Large Language Model through SAP's AI Core Generative AI Hub, Smart Legal Lens enables legal teams to make faster, more informed decisions while reducing the risk of overlooking crucial contract details during M&A transactions.
lab2dev
CleanCo GenAI is an application that aids in developing business requirements following Clean Core principles. It features a Clean Core Assistant that understands both In-App and Side-by-Side Extensibility, helping customers choose optimal implementation approaches. The solution aids in creating RFPs, generates project estimates, and suggests consultant profiles for extension development. The application leverages SAP BTP features, Best Practices, and lab2dev’s extensive experience with SAP S/4HANA extension projects. It recommends appropriate extension types aligned with Clean Core principles, identifies required BTP components, and suggests necessary APIs for development. The technical architecture combines SAP UI5 for frontend development with SAP Cloud Application Programming Model (CAP), utilizing SAP HANA Vector Engine and Generative AI Hub with Open AI. The solution incorporates expertise from lab2dev, SAP Best Practices, and SAP Business Hub APIs.
Capgemini
Churn Shield AI is a AI Solution developed to help e-commerce and retail companies reduce customer attrition through predictive analytics and personalized engagement. Churn Shield leverages historical customer data and sentiment analysis to identify at-risk customers and create tailored retention strategies. Powered by SAP's AI Core and GPT-4o model, the solution automatically generates personalized retention offers and analyzes customer feedback to gauge satisfaction levels. The system integrates seamlessly with SAP S/4HANA and SAP Billing and Revenue Innovation Management (BRIM), while utilizing SAP HANA Vector Engine for efficient storage and processing of consumption data and billing documents. This comprehensive approach enables businesses to proactively address customer concerns, optimize retention campaigns, and maintain a loyal customer base through data-driven decision-making and automated personalization.
Group3
The following partners from Asia Pacific Japan and Middle and Eastern Europe emerged as winners in the third demo jam session, presented in order of Winner and Joint Runners-up.
cbs Consulting
The cbs LTSD-AID (Long Term Supplier Declaration – Advanced Integration for Documents) prototype integrates data from complex, non-standardized documents into SAP. It handles various document types and layouts, such as LTSDs in the GTS area. An open-source custom OCR on SAP AI Core extracts (meta)data, discarding over 90% of unnecessary data. The remaining data is mapped to the SAP data structure and secured by two Large Language Models (LLMs), Mixtral and gpt4-o, via the SAP GenAI Hub. Built with SAP Cloud Application Programming Model (CAP), Python microservices, and AI Core, it integrates with SAP S/4HANA. This solution helps customers comply with international trade agreements and improves efficiency in processing high-volume LTSD documents. GTS clerks only validate results instead of manually transferring all data into SAP GTS.
IBM
The GenAI-based Fraud Detection in Medical Grants solution, developed by IBM as part of Hack2Build, tackles the business challenge of fraud detection in medical grants by leveraging Generative AI and Large Language Models (LLMs) to analyze contract documents and invoices. This solution extracts relevant information, such as vendor names, addresses, and amounts, and compares them to detect discrepancies. It also compares actual vendor details and bank key details from SAP S/4HANA, highlighting discrepancies for auditors to review. Built using the SAP Cloud Application Programming Model (CAP) application, SAP Analytics Cloud, SAP HANA Vector Engine, SAP AI Core, and SAP HANA cloud, the prototype offers a fast, cost-effective, and thorough solution for detecting potential fraud. The solution features a user-friendly interface that visualizes differences between vendor name, address, and amount, reducing the risk of fraudulent activities.
GenAI-based Fraud Detection in Medical Grants by IBM
KPMG
The prototype, C.O.A.L.A (Certificate of Analysis Leveraging Artificial Intelligence), addresses the challenges of manual and error-prone processing of Certificates of Analysis (COAs) in the food and beverage industry, life sciences & chemical industries. The solution leverages SAP Business AI, specifically Generative AI Hub and Retrieval Augmented Generation (RAG), to automate the extraction of information from COAs, detect and translate different languages from different formats of COAs and perform system checks and validations using enterprise data. The prototype features a user-friendly interface, leveraging SAP Build, and integrates E2E Inbound quality process with SAP ERP to post inspection lot results. It has built-in exception handling capabilities. The solution aims to increase operational efficiency, reduce errors, and save costs for clients. The business benefits of the prototype include the potential to automate millions of pages of manual process, with huge savings per year.
Panel of Judges
We extend our sincere thanks to the judges who lent their expertise to this initiative. Over three demo jam sessions, senior leaders and experts from SAP Business AI, SAP BTP, and Partner Ecosystem Success carefully evaluated 10-minute pitches from participating partners. They assessed each solution’s potential to address real-world challenges using SAP Business AI and provided thoughtful feedback to help partners further refine their solutions in the next phase of Hack2Build.
| Frank Ruland | Vice President, Global Head of Industry Partner Management |
| Georg Fischer | Chief Product Manager SAP BTP |
| Gianluigi Bagnoli | Global VP, BTP Solution Architects, Partner Solution Success |
| Holger Brammer | VP, Business Development SAP AI Partner Ecosystem |
| Kathrin Hettel | Vice President, Strategic Cross-Portfolio & AI Partnership at SAP |
| Marc-Oliver Klein | Vice President, Head of Partner Product Management & Strategic AI Development Partnerships |
| Mir Aliullhadi Hares | Lead Product Manager – Generative AI Hub / SAP AI Core / SAP AI Launchpad |
| Pavel Penaz | Global Vice President & Head of Partner Solution Success BTP & AI |
| Rajeev Gollapudi | Chief Product Manager, SAP BTP Product Management |
| Rudi Held | Vice President, Global Head of SAP Co-Innovation Lab Network, PES |
| Steffen Schad | Head of Outbound PM, SAP BTP |
| Suresh Kumar Raju | Head of Engineering, SAP AI Core & Launchpad, APJ |
Special Thanks
We extend our appreciation to the SAP team members from SAP Business AI, BTP Architecture, Strategic Partner Enablement, and SAP Co-Innovation Lab, whose expertise guided partners to successfully develop their solutions during the Hack2Build SAP Business AI initiative.
Way Forward
Hack2Build consists of two phases: the hack phase and the build phase. All selected partners in this initiative will continue working with SAP, maintaining momentum in this co-innovation journey. SAP will engage with partners who demonstrate continued interest and the necessary capacity to expand their business AI solutions into comprehensive offerings for customers. Additionally, SAP will guide partners through the solution certification process and help make these solutions accessible to customers via various partner market channels.
SAP AI Core SAP Business Technology Platform
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