27 docs tagged with "Google Cloud Platform"

The Agent2Agent (A2A) protocol facilitates communication between independent AI agents. SAP contributes to the A2A specification via Joule and Open Resource Discovery (ORD).

Agents for Structured Data leverage advanced AI capabilities to transform how organizations interact with and derive insights from large quantities of tabular and other structured data. By integrating natural language processing, federated data access, and real-time analytics, these applications enable seamless decision-making and operational efficiency across diverse industries.

This is an overview of AI agents and their role in enterprise automation, focusing on SAP's Project Agent Builder (PAB) and its support for content-based and code-based agent development. It explores the technical components, design strategies, and evaluation criteria for deploying AI agents effectively within the SAP ecosystem.

Enhance SAP BTP applications using Generative AI by integrating custom prompts for Foundation Models or LLMs. This allows natural language processing to craft AI responses tailored to specific tasks, enabling intelligent user interactions and achieving application objectives.

The purpose of Data Products in the context of SAP is the efficient and standardized sharing and consumption of data across applications and domains. It helps ensure high-quality metadata, is optimized for intensive reads, and describes the lineage and interfaces available for integration.

Explore the reference architecture for deploying SAP Integration Suite - Edge Integration Cell on GCP. Learn about the required resources, and key considerations for setup and implementation on GCP.

Discover reference architectures for deploying SAP Integration Suite - Edge Integration Cell on hyperscalers. Access architecture diagrams and key resources to understand its setup and implementation.

Semantic search using embeddings converts data into dense numeric vectors to capture meanings. Stored in vector databases, these vectors enable efficient similarity searches with cosine similarity, improving search relevance and user experience by focusing on meaning over exact keywords.

SAP Build Work Zone offers a comprehensive solution architecture designed to elevate user productivity and engagement by providing a digital workplace platform that supports single-sign-on. This innovative approach centralizes access to essential business applications, processes, information, and communication, serving as a unified entry point accessible from desktop or mobile devices. It harmonizes business content, applications, workflows, and processes across your landscape, ensuring a seamless integration and interaction within your digital ecosystem.

Guidance for setting up SAP Task Center service on SAP BTP. Learn about the architecture components and flow in this architecture.

SAP Datasphere's data integration architectures that harmonizes SAP and non-SAP data using data fabric architecture helps business experts to make data-driven decisions with unprecedented impact.

The SAP Federated Machine Learning Python library (FedML) applies the data federation architecture of SAP Datasphere for intelligently sourcing SAP and non-SAP data for Machine Learning experiments, run on any Machine Learning platform, thereby removing the need for replication or data movement. By abstracting data connection, data discovery, data loading (for all ML platforms), model training, model deployment, and inferencing (for hyperscaler machine learning platforms), the FedML library offers end-to-end integration with just a few lines of code.

FedML-GCP provides end-to-end integraton for training models in Google Vertex AI using live business data from SAP systems and eliminates the need for duplicating the data.

Harness Generative AI on SAP BTP using a CAP-based backend with SAP HANA Cloud's Vector Engine for similarity search. The Generative AI Hub allows seamless integration of LLMs, supporting RAG and other advanced patterns. Compatible with Cloud Foundry and Kyma, it optimizes AI-driven app development.

Insight Apps are delivered in SAP Business Data Cloud as a prebuilt set of artifacts, from Data Products, to models, to stories in SAP Analytics Cloud. They allow you to configure your entire environment simply by subscribing.

SAP Build Process Automation is a no-code/low-code solution for automating business processes. Integrate SAP and non-SAP systems across cloud and hybrid landscapes with features like workflow management, robotic process automation, and predefined content. Streamline tasks such as scheduling agreements, job requisitions, and data management, enhancing productivity and reducing manual effort.

Data from Google Cloud Platform (GCP) data services can be seamlessly integrated and harmonized with both SAP and non-SAP data using SAP Datasphere's advanced data fabric architecture.

This reference architecture demonstrates a common use case for integrating various types of data—structured, semi-structured, and unstructured—into SAP HANA Cloud, utilizing the powerful features of SAP HANA Cloud Data Lake. By implementing this architecture, businesses can meet the challenge of providing a modern data foundation for intelligent data applications and provide cost-effective data management and analytics across the enterprise.

Modernize SAP Business Warehouse (BW) with SAP Business Data Cloud (BDC) to unlock real-time analytics, AI-driven insights, and scalable cloud-native architecture. Leverage SAP Datasphere, SAP Analytics Cloud, and data products to transition seamlessly while preserving existing investments. Discover structured migration pathways, advanced AI/ML capabilities, and unified data management for future-ready enterprise data strategies.

Enhance LLM control with Retrieval Augmented Generation (RAG), which integrates external data to reduce hallucinations and improve accuracy across multiple domains without the need for fine-tuning. This approach combines factual data with language knowledge for increased precision.

SAP and Databricks have partnered to integrate SAP data with Databricks AI and analytics platform, allowing businesses to leverage SAP data for AI and machine learning applications. This partnership simplifies data access and eliminates the need for complex ETL processes, enabling real-time analytics and AI-driven decision-making.

The reference architecture for Esri running on SAP HANA Cloud as a geodatabase represents a powerful integration of geospatial technology with enterprise-grade cloud infrastructure. This enhances geospatial capabilities by allowing organizations to store, process, and analyze spatial data directly within SAP HANA Cloud, utilizing its multimodel processing and built-in spatial engine. The integration provides real-time access to both SAP and non-SAP data, breaking down data silos and enabling near-instant insights, which is crucial for industries like utilities during natural disasters.

This architecture outlines a cloud-agnostic approach for securely consuming services offered by hyperscalers from applications running outside their environments.

Configure secure, keyless access to GCP resources using OIDC-based Workload Identity Federation. Workloads authenticate without storing service account keys.

Discover SAP BDC and S/4HANA integration with SAP-managed Data Products and Insight Apps for advanced analytics. Learn how to produce, activate, and visualize data products using SAP Datasphere and SAP Analytics Cloud. Explore pre-built Insight Apps for actionable intelligence across Core Enterprise, People, Spend, Customer, and Supply Chain Analytics. Maximize business insights with SAP's trusted data foundation and lifecycle management. Optimize decision-making with SAP's seamless architecture.

SAP Business Data Cloud (BDC) unifies SAP and non-SAP data, enabling advanced analytics, governance, and AI-driven insights. With tools like SAP Datasphere, SAP Analytics Cloud, and Databricks integration, SAP BDC addresses data silos, improves data quality, and supports real-time processing. Modernize legacy systems, create reusable data products, and leverage a unified semantic model for scalable, future-ready enterprise data strategies.

Designing and operating cloud based solutions in a multi-regional setup are technically advanced tasks. The solution and application design, usage of different network providers and last but not least the geographical placement of services have an impact on the overall performance.