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AI-assisted full stack development using model context protocol serversAI-assisted full stack development using model context protocol serversMCP servers in Visual Studio Code used to configure, query and change a full-stack application built with CAP, CDS and OData: the agent access to your code concern, a coding assistant reading and changing the project it works in. The abstract names no server, so neither @cap-js/mcp-server nor any other is attached, and it does not say which changes are made. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Sergio Guerrero, written here from SAP's abstract; the recording is not yet published.
Consume Remote Services in a Full-Stack CAP ApplicationConsume Remote Services in a Full-Stack CAP ApplicationExtending the Developer's Guide application with a remote S/4HANA service — connectivity, importing the Business Partner API, and running against it. SAP publishes this as four separate paths: mock server or real S/4HANA Cloud, times Cloud Foundry or Kyma. One entry covers all four, because the difference between them is which backend and which runtime, not what you learn.SAP
Extend SAP SuccessFactors on SAP BTP with the SAP Cloud Application Programming ModelExtend SAP SuccessFactors on SAP BTP with the SAP Cloud Application Programming ModelTwelve tutorials, about two hours, building a side-by-side extension of SuccessFactors on BTP. The spine is remote services: importing the SuccessFactors OData service definitions into a CAP model, then treating them as entities the extension reads and writes through, rather than as an API called from a handler. Indexed as one entry because the parts only make sense in order.SAP
OData entity as a governed query surface for agents, not a toolOData entity as a governed query surface for agents, not a toolAn OData entity, generated from the annotations a service already carries, as the surface an agent queries over SAP data: filterable, selectable and sortable fields, authorisation injected on the server side, and a bound query cost, instead of the entity as a tool. SAP's abstract sets this against the MCP gateway in SAP Integration Suite, where exposing an API is the easy part and getting an agent to pick the right one is not, which is the tool governance concern read through OData. A TechEd 2026 session (Wednesday 28 October, Berlin), presented by Aleksandr Ivanov and Evgenii Shirokikh, written here from SAP's abstract; the recording is not yet published.
SAP Fiori elements and the age of AI: Build apps that are future readySAP Fiori elements and the age of AI: Build apps that are future readyBuilding SAP Fiori elements apps so they work with AI and fit SAP's next products: the abstract names AI-assisted development, OData and annotation design, and intent- and action-ready semantics that keep an app secure, discoverable and upgrade safe. Annotation design is the Fiori annotations concern and the OData service under it the other; the atlas holds no entry for SAP Fiori elements itself, and the abstract names no tool, annotation or version. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Katja Zoch and Sebastian Steinhauer, written here from SAP's abstract; the recording is not yet published.
Add MCP capabilities to a CAP serviceAdd MCP capabilities to a CAP serviceA fifteen-minute walkthrough of turning a plain CAP service into an MCP server: annotate the service with @mcp, install @cap-js/mcp, and it is served alongside OData at /mcp/<path>. The part worth reading it for is what happens next — cds watch writes the endpoint into the local agent's own configuration file, so OpenCode or Claude Code can call the service without anyone editing JSON by hand. It is built on the tiny-sample facet, so there is nothing to prepare, and it shows the protocol traffic rather than only the result. Written while the adapter was in beta, and it says so.published 2026-08-13
Agentic AI & AI AgentsAgentic AI & AI AgentsSAP's target picture for AI agents: Joule as the engagement layer — Joule Work, Joule Assistants, Joule Agents — with custom agents from customers, partners and SAP teams connecting through A2A for agent-to-agent collaboration and MCP for tool connectivity, on the SAP Business AI Platform. It says up front that parts are not generally available yet, in particular bidirectional communication with third-party agents through the Agent Gateway, so it reads as direction with the building blocks named rather than a design to copy today.published 2026-08-27
AI-native North Star architecture — Platform LayerAI-native North Star architecture — Platform LayerThe platform layer of SAP's North Star architecture, the chapter that says where agents run and what a developer builds them with. It names an AI Golden Path built on the SAP Cloud Application Programming Model, the ABAP Cloud development model with RAP and the SAP Fiori design system, and a managed agent runtime on SAP BTP that is designed to provide software development kits for building agents in any framework, an agent sandbox, container-hosted execution, a skills registry and continuous evaluations, which is the ground agent tooling covers. Agents are extended without changing their code through four patterns, the first of them tool extensibility through the Model Context Protocol, the concern MCP servers is named for; the process-layer chapter adds that a pro-code path with a standardised agent SDK and a prompt-driven path through the Joule Studio solution produce the same code artifact on the same runtime. It describes a design SAP intends rather than products that exist, and the SDK and the registry it names have no entry here yet.published 2026-05-13
AI-native North Star architecture — Platform Layer
Agent tooling changed in @cap-js/agents 0.9.1, 2026-08-14. Affects A reference.
Examine the details of the Model Context Protocol on startupExamine the details of the Model Context Protocol on startupWhat the MCP adapter actually does when a CAP server boots, watched rather than described — the companion to the tutorial that switches it on.
HANA AI Toolkit — Local MCP ServerHANA AI Toolkit — Local MCP ServerAn MCP server that turns the hana-ml Python library into governed tools an agent can call against a HANA Cloud instance, shipped in the hana-ai toolkit and exposed over stdio, SSE and streamable HTTP. Its one firm rule is attributable execution: an audit module writes the MCP-side identity — agent, model, session, tool, redacted arguments — into the HANA connection before any SQL runs, and fails the call if that write fails. A worked example of governance on an MCP tool surface, from SAP's data side rather than CAP's.published 2026-06-15
Third-Party MCP Server Access to SAP Solutions on BTPThird-Party MCP Server Access to SAP Solutions on BTPDescribes external MCP servers and custom servers on BTP, assigning their operators responsibility for authentication, scoped identity, API limits, logging and lifecycle. The permitted use remains conditional on the SAP API Policy, while SAP Integration Suite and Joule Studio are described as SAP-provided paths. Hosting a server on BTP does not automatically supply its governance controls.Dhawal Joshi, Harut Ter-Minasyan, Mirko Günther
Explore your Hyperscaler data with SAP Business Data CloudExplore your Hyperscaler data with SAP Business Data CloudSAP's map of the ways data held on hyperscaler and partner platforms is joined with SAP data in SAP Business Data Cloud, with a sub-page each for AWS, Azure, Google Cloud, Databricks and Snowflake. It sets four modes side by side: BDC Connect shares data products in both directions over the Delta Sharing protocol from the object store layer, while in the SAP Datasphere layer federation reads remote tables in place, Replication Flows copy SAP data out to stores such as Amazon S3 or Google BigQuery, and Data Flows import files and transform them into Datasphere tables, the last three being the ground loading a warehouse covers. The Snowflake and BigQuery connectors are dated to 2026 releases, and a closing page lists what slows federation, from source and tenant in different regions to queries that do not filter and aggregate at the source.published 2026-05-08
Federated Machine Learning with SAP DatasphereFederated Machine Learning with SAP DatasphereSAP's design for training predictive models on an external machine learning platform against SAP Datasphere data that is not replicated to that platform. The open-source FedML Python library runs in the platform's notebook, connects to Datasphere over Python/SQLDBC and reads the analytic models in which Datasphere unifies SAP and non-SAP sources; a trained model can then be deployed to SAP AI Core, or in several sub-pages to SAP BTP, Kyma runtime, which is the predictive models path where training happens outside SAP. Sub-pages cover Amazon SageMaker, Azure Machine Learning, Google Vertex AI, Databricks, NVIDIA RAPIDS on GPUs and IBM watsonx.published 2025-01-23
Flexible analytics at speed: Calculation views in SAP Business Data CloudFlexible analytics at speed: Calculation views in SAP Business Data CloudCalculation views in SAP HANA Cloud, the reusable analytic modelling blocks built in its graphical modelling environment, with three newer parts the abstract names: AI-assisted modelling, refactoring, and advanced materialisation, and the way the views sit inside SAP Business Data Cloud. What a materialisation is chosen on, and what the AI assistance generates, is not stated. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Hansika Colomboge Dona, Jan Zwickel, Niklas Siemer and Thomas Hammer, written here from SAP's abstract; the recording is not yet published.
Agent-to-agent in action: SAP and Adobe CX Enterprise Coworker at HenkelAgent-to-agent in action: SAP and Adobe CX Enterprise Coworker at HenkelA customer story: SAP's data agents and SAP Business Data Cloud with Adobe CX Enterprise Coworker putting enterprise data in front of Henkel's marketing teams, with faster decisions as the stated result. The abstract names Business Data Cloud as the data side of an agent-to-agent setup and says nothing about what it does there or how the two agents talk; neither Adobe's product nor the data agents are atlas entries. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Ankur Jain, Ramalingam Ramani and Thomas Hammer, written here from SAP's abstract; the recording is not yet published.
Agentic SAP BW modernization: Your path to SAP Business Data CloudAgentic SAP BW modernization: Your path to SAP Business Data CloudStrategies for moving from SAP Business Warehouse to SAP Business Data Cloud, with dedicated migration tools and AI agents to shorten the move while keeping what was built in SAP BW, the platform migration concern for a warehouse. A Fresenius speaker co-presents; the abstract names neither the migration tools nor the agents. A TechEd 2026 session (Wednesday 28 October, Berlin), presented by Constantin Herbst, Hannes Keil and Sandy Tran, written here from SAP's abstract; the recording is not yet published.
AI-enhanced analytics with SAP Business AI PlatformAI-enhanced analytics with SAP Business AI PlatformSAP Business Data Cloud data products joined to an ontology, a semantic layer the abstract says is supported by the Model Context Protocol, and read from Joule Work (SAP Joule) and SAP Analytics Cloud: that is the architecture SAP's abstract states for its AI-enabled analytics. The abstract names the parts and not how the semantic layer is modelled or what an analytics developer builds against. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Hacen Benkhedah, Joaquin Recio Huertas, Matilda Hyka and Oliver Huth, written here from SAP's abstract; the recording is not yet published.
Architecting your data foundation for the Autonomous EnterpriseArchitecting your data foundation for the Autonomous EnterpriseBuilding a data foundation for what SAP calls the Autonomous Enterprise on SAP Business Data Cloud: a business data fabric that unifies trusted data, business context and governed data products across an organisation's systems, so that Joule Agents in SAP Joule have the context their answers rest on. The abstract states Business Data Cloud's role and no product, data product or integration beneath it. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Mudit Mittal and Prakash Nanduri, written here from SAP's abstract; the recording is not yet published.
Build agentic SAP extensions with Google CloudBuild agentic SAP extensions with Google CloudGoogle Cloud's architectures for agentic AI apps on SAP with a clean core: SAP Business AI Platform, SAP S/4HANA and SAP Business Data Cloud joined with BigQuery, Gemini and Google's Agent Development Kit. The abstract names zero-copy data agents, developer API workflows and ABAP extensions for AI integration, the last of which is the Extensibility concern; Business Data Cloud is the one atlas entry it names, and how any piece connects to another is not stated. A TechEd 2026 session (Wednesday 28 October, Berlin), presented by Ekaterina Kruse, Ian Moria and Stany Winkler, written here from SAP's abstract; the recording is not yet published.
Build AI agents on SAP and non-SAP data and context in an open lakehouseBuild AI agents on SAP and non-SAP data and context in an open lakehouseSAP Business Data Cloud as an open lakehouse: the abstract states that it holds third-party data beside SAP data and its semantic context on Apache Iceberg and Apache Polaris, that architects and developers publish governed data products and ontologies from it, which is the cataloguing and lineage concern, and that agents built on them for SAP Joule can be reached from outside over A2A. How a data product is defined, and what the ontology layer adds to it, is not in the abstract. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Rahim Bhojani and Sivakumar N, written here from SAP's abstract; the recording is not yet published.
Build and govern data products in the Joule Studio solutionBuild and govern data products in the Joule Studio solutionData products in SAP Business Data Cloud are built and deployed from Joule Studio, in SAP's abstract, with no-code, AI-assisted tools that combine SAP and third-party data, and are then governed, catalogued and shared for analytics and AI, the cataloguing and lineage concern on the product side. The abstract names the steps and not what a data product built this way contains or how Joule Studio reaches the data. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Arne Ludwig, Aruna Kashinath, Rene Kirchhoff and Sandy Tran, written here from SAP's abstract; the recording is not yet published.
Build real-time, unified data products for agentic AI with SAP ReltioBuild real-time, unified data products for agentic AI with SAP ReltioSAP Reltio inside SAP Business Data Cloud unifies master data across SAP and third-party systems and complements SAP Master Data Governance, in SAP's abstract, with Customer 360 as the named scenario and real-time data products for applications, analytics and AI as the output. The abstract states Reltio's place in the product and nothing about how the unification or the data products work. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Arne Ludwig, Rene Kirchhoff, Richard Mooney and Sriraj Rajaram, written here from SAP's abstract; the recording is not yet published.
Enhancing agentic AI with trusted business dataEnhancing agentic AI with trusted business dataHow SAP Business Data Cloud gives AI applications and agents governed access to business data and its context, and how zero-copy architectures let AI read enterprise data with less of it moved, which is the data federation concern. The abstract names the product and the architecture and states no mechanism or product the zero-copy path runs over. A TechEd 2026 session (Tuesday 27 October, Berlin; also DA100V, virtual), presented by Aruna Kashinath, Hannes Keil and San Tran, written here from SAP's abstract; the recording is not yet published.
Enriching AI models with SAP AI Core in SAP Business Data CloudEnriching AI models with SAP AI Core in SAP Business Data CloudThe integration between SAP Business Data Cloud and SAP AI Core, through which data products with their semantics feed AI models for benchmarking, custom AI development and agentic analytics and applications. The abstract names the two products and the three uses and states nothing about how the data reaches AI Core or what the integration consists of. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by San Tran and Sandy Tran, written here from SAP's abstract; the recording is not yet published.
Explore your Hyperscaler data with SAP Business Data CloudExplore your Hyperscaler data with SAP Business Data CloudSAP's map of the ways data held on hyperscaler and partner platforms is joined with SAP data in SAP Business Data Cloud, with a sub-page each for AWS, Azure, Google Cloud, Databricks and Snowflake. It sets four modes side by side: BDC Connect shares data products in both directions over the Delta Sharing protocol from the object store layer, while in the SAP Datasphere layer federation reads remote tables in place, Replication Flows copy SAP data out to stores such as Amazon S3 or Google BigQuery, and Data Flows import files and transform them into Datasphere tables, the last three being the ground loading a warehouse covers. The Snowflake and BigQuery connectors are dated to 2026 releases, and a closing page lists what slows federation, from source and tenant in different regions to queries that do not filter and aggregate at the source.published 2026-05-08
Joule and SAP Knowledge Graph: Context-aware AI across SAP solutionsJoule and SAP Knowledge Graph: Context-aware AI across SAP solutionsThe catalogue carries RA107's abstract under this title, and what it describes is SAP AI Core as the management and orchestration layer of an AI architecture: extending Joule Agents in SAP Joule, the model library in Joule Studio for contextual reasoning, connecting data products from SAP Business Data Cloud, and embedding AI in SAP S/4HANA. The SAP Knowledge Graph the title names does not appear in that text, so the edges rest on the abstract as published, and whether the session follows the title or the abstract is not known until it is recorded. A TechEd 2026 session (Wednesday 28 October, Berlin; also RA110V, virtual), presented by Jan Portisch and Pavithra G K, written here from SAP's abstract; the recording is not yet published.
Reimagining master data as the foundation for enterprise AIReimagining master data as the foundation for enterprise AIMaster data as the foundation for AI: SAP Business Data Cloud unifying, governing and delivering master data as reusable data products, the cataloguing and lineage concern, for analytics, autonomous applications and AI that share one business context. The abstract names no component of Business Data Cloud and no master data product, and Reltio, the co-presenter's company, is not named in it. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Arne Ludwig and Sriraj Rajaram, written here from SAP's abstract; the recording is not yet published.
Road map for SAP HANA Cloud: What’s next for the AI databaseRoad map for SAP HANA Cloud: What’s next for the AI databaseSAP's road map for SAP HANA Cloud, which the abstract places as a core component of SAP Business AI Platform within SAP Business Data Cloud. The abstract promises a firsthand look at what is next for the database and names no feature, release or date, so the two edges rest on the products it names and nothing more. A TechEd 2026 session (Wednesday 28 October, Berlin), presented by Niklas Siemer and Thomas Hammer, written here from SAP's abstract; the recording is not yet published.
SAP HANA Cloud as the AI database for SAP Business Data CloudSAP HANA Cloud as the AI database for SAP Business Data CloudSAP HANA Cloud as the AI database at the centre of SAP Business Data Cloud: the strategy behind its AI-first direction, and a Carl Zeiss speaker on how it runs in production today. The abstract names the two products and the customer and no feature, workload or figure, so the edges rest on the products as its subject. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Kush Kashyap and Thomas Hammer, written here from SAP's abstract; the recording is not yet published.
Share data products with zero copies using SAP Business Data Cloud ConnectShare data products with zero copies using SAP Business Data Cloud ConnectSAP Business Data Cloud Connect shares data products between SAP Business Data Cloud and third-party platforms with zero-copy access, in both directions and for metadata as well as data, in SAP's abstract, with the business context kept on the way. The abstract names the product and its two properties, bidirectional and zero-copy, and does not say which third-party platforms or which protocol carry the sharing. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Babacar Toure, Hannes Keil, Maria Uruena and Neetha Pucknat, written here from SAP's abstract; the recording is not yet published.
The future of the SAP Business Data Cloud solution: Data and AI road mapThe future of the SAP Business Data Cloud solution: Data and AI road mapThe road map for SAP Business Data Cloud as the data foundation of SAP Business AI Platform: upcoming work in data products, AI models and agentic analytics, framed as activating business context and running autonomous processes. A road map session, so nothing in it ships yet, and the abstract names the three areas and no item within them; a Fresenius speaker co-presents. A TechEd 2026 session (Tuesday 27 October, Berlin; also DA802V, virtual), presented by Constantin Herbst and Prakash Nanduri, written here from SAP's abstract; the recording is not yet published.
The next evolution of SAP Business Data Cloud with Dremio and SAP ReltioThe next evolution of SAP Business Data Cloud with Dremio and SAP ReltioSAP Business Data Cloud's data fabric with two additions SAP's abstract names, Dremio and SAP Reltio: data products, open catalogues, unified master data and business semantics as the pieces of a data foundation for analytics and agentic AI. The abstract names the two products and not what each takes over in the fabric. A TechEd 2026 session (Wednesday 28 October, Berlin), presented by Florian Schmidt, Rene Kirchhoff and Sriraj Rajaram, written here from SAP's abstract; the recording is not yet published.
Transforming Enterprise Data Strategy with SAP Business Data CloudTransforming Enterprise Data Strategy with SAP Business Data CloudSAP's layered picture of SAP Business Data Cloud, from lake storage and compute up to a knowledge core and agents, with eight sub-pages that each work one part through. The data products page is the cataloguing and lineage part: datasets described by Open Resource Discovery metadata, listed in the BDC catalog and shared over Delta Sharing to SAP Databricks and SAP HANA Cloud, with SAP Datasphere as a consumer on the intelligent content page; other pages install intelligent content, bring SAP BW data in through the Data Product Generator, provision groups by SCIM from Cloud Identity Services into SAP Databricks, which is identity provisioning, and train predictive models in SAP Databricks that SAP AI Core then serves for batch and real-time scoring. The main page states direction more than mechanism, and the BW page marks SQL Share for derived and OData for analytical data products as to be available.published 2026-05-12
What’s next for agentic analytics and planning in SAP Business Data CloudWhat’s next for agentic analytics and planning in SAP Business Data CloudWhat is next for agentic analytics and planning in SAP Business Data Cloud: SAP Joule's agents automating insight delivery, analysis, narrative generation and modelling tasks. A road map session; the abstract names the four kinds of task and no agent or date. A TechEd 2026 session (Tuesday 27 October, Berlin; also DA806V, virtual), presented by Kristian Ruemmelin, written here from SAP's abstract; the recording is not yet published.
Enhancing agentic AI with trusted business dataEnhancing agentic AI with trusted business dataHow SAP Business Data Cloud gives AI applications and agents governed access to business data and its context, and how zero-copy architectures let AI read enterprise data with less of it moved, which is the data federation concern. The abstract names the product and the architecture and states no mechanism or product the zero-copy path runs over. A TechEd 2026 session (Tuesday 27 October, Berlin; also DA100V, virtual), presented by Aruna Kashinath, Hannes Keil and San Tran, written here from SAP's abstract; the recording is not yet published.
Under the hood of the Delta Sharing protocolUnder the hood of the Delta Sharing protocolHow a Delta Sharing server, dsserv, implements the open-source Delta Sharing protocol for zero-copy sharing: Delta tables ingested, governed and streamed live from local S3-compatible storage into cloud consumers such as Databricks. Neither the server nor the protocol is an atlas entry; the edges are to data federation, the concern zero-copy sharing answers, and to object storage, where the tables sit, and the abstract names no SAP product. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Philipp Nell, written here from SAP's abstract; the recording is not yet published.
Analyze and optimize ABAP Cloud model apps built on core data servicesAnalyze and optimize ABAP Cloud model apps built on core data servicesPerformance anti-patterns in data models built with ABAP CDS under ABAP Cloud applications, and the tools that find them: the abstract names ABAP cross trace, the SQL analyzer (PlanViz) in Visual Studio Code and the SAP HANA database explorer as what the session uses to follow a bottleneck from the application to the database. The anti-patterns are taken from real business applications, which is where the data modelling edge holds; which ones are shown is not in the abstract. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Ingo Braeuninger, Robert Werlich, Steffen Siegmund and Thomas Fiedler, written here from SAP's abstract; the recording is not yet published.
Explore the declarative power of status-transition flowsExplore the declarative power of status-transition flowsModelling which state a record may move to next, declaratively, rather than scattering the rule across the handlers that move it.SAP
Learn how to define constraints declaratively in your CDS modelLearn how to define constraints declaratively in your CDS modelConstraints expressed in the model rather than checked in a handler — the distinction the atlas draws between input validation the framework enforces and validation somebody writes.SAP
Agentic memory: Knowledge graph engine and recall in SAP HANA CloudAgentic memory: Knowledge graph engine and recall in SAP HANA CloudThe knowledge graph engine in SAP HANA Cloud as an agent's memory: what the engine, the graph side of graph, spatial and document data, does in an agentic workflow, how an agent keeps what it learns there, the state agent tooling holds between turns, and the SAP AI Core integration through which the database calls LLMs and tabular foundation models such as SAP-RPT-1. The abstract names the engine, the memory role and the AI Core link and does not say how the memory is written or read. DA263 on Wednesday 28 October is a two-hour hands-on on the same engine with a different cast. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Markus Fath and Shraddha Shetty, written here from SAP's abstract; the recording is not yet published.
Analyze and optimize ABAP Cloud model apps built on core data servicesAnalyze and optimize ABAP Cloud model apps built on core data servicesPerformance anti-patterns in data models built with ABAP CDS under ABAP Cloud applications, and the tools that find them: the abstract names ABAP cross trace, the SQL analyzer (PlanViz) in Visual Studio Code and the SAP HANA database explorer as what the session uses to follow a bottleneck from the application to the database. The anti-patterns are taken from real business applications, which is where the data modelling edge holds; which ones are shown is not in the abstract. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Ingo Braeuninger, Robert Werlich, Steffen Siegmund and Thomas Fiedler, written here from SAP's abstract; the recording is not yet published.
Build AI agents and applications natively on SAP HANA CloudBuild AI agents and applications natively on SAP HANA CloudSAP HANA Cloud as the base for agentic applications on SAP Business AI Platform: the session goes through CAP, the SAP HANA Cloud vector engine and SAP AI Core, with architecture patterns and lessons learned from building AI-supported applications. SAP's abstract names the three parts of that stack and the vector engine as the database's feature in it, and describes none of the patterns. A TechEd 2026 session (Wednesday 28 October, Berlin; also DA113V, virtual), presented by Christoph Morgen and Shraddha Shetty, written here from SAP's abstract; the recording is not yet published.
Build your custom knowledge layer with SAP HANA CloudBuild your custom knowledge layer with SAP HANA CloudSAP HANA Cloud's multi-model engines, the knowledge graph engine among them, as the base for a custom knowledge layer over the enterprise's data, with SAP Business Data Cloud as the product that includes the database. Graph, spatial and document data put to an AI use; the abstract names the graph engine and not the query language or the vector side. A TechEd 2026 session (Wednesday 28 October, Berlin; also ST108V, virtual), presented by Niklas Siemer and Sebastian Schmidt, written here from SAP's abstract; the recording is not yet published.
Flexible analytics at speed: Calculation views in SAP Business Data CloudFlexible analytics at speed: Calculation views in SAP Business Data CloudCalculation views in SAP HANA Cloud, the reusable analytic modelling blocks built in its graphical modelling environment, with three newer parts the abstract names: AI-assisted modelling, refactoring, and advanced materialisation, and the way the views sit inside SAP Business Data Cloud. What a materialisation is chosen on, and what the AI assistance generates, is not stated. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Hansika Colomboge Dona, Jan Zwickel, Niklas Siemer and Thomas Hammer, written here from SAP's abstract; the recording is not yet published.
Medallion Reference Architecture for Big Data Processing in SAP HANA CloudMedallion Reference Architecture for Big Data Processing in SAP HANA CloudSAP's medallion layout for SAP HANA Cloud: structured, semi-structured and unstructured data lands raw in HANA Cloud, data lake files as the bronze layer, is cleansed into a common structure in silver, held in data lake files or the HANA database, and is curated and read-optimised in gold, from where it can also be exposed as a Delta Share. The staged path from raw to consumable is the ground loading a warehouse covers, with Spark jobs and SAP Datasphere data flows named as ways to move data between layers and SAP Analytics Cloud among the consumers of gold. It leaves the ingestion method open, to be chosen by source, freshness and performance, and names no pipeline or schedule beyond that.published 2025-04-03
Modernize your database landscape with SAP HANA CloudModernize your database landscape with SAP HANA CloudWhy to move a database estate to SAP HANA Cloud, and the migration tools and services for doing so, which is the platform migration concern. SAP's abstract is one sentence and names none of the tools. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Niklas Siemer and Roman Belosludtsev, written here from SAP's abstract; the recording is not yet published.
Road map for SAP HANA Cloud: What’s next for the AI databaseRoad map for SAP HANA Cloud: What’s next for the AI databaseSAP's road map for SAP HANA Cloud, which the abstract places as a core component of SAP Business AI Platform within SAP Business Data Cloud. The abstract promises a firsthand look at what is next for the database and names no feature, release or date, so the two edges rest on the products it names and nothing more. A TechEd 2026 session (Wednesday 28 October, Berlin), presented by Niklas Siemer and Thomas Hammer, written here from SAP's abstract; the recording is not yet published.
SAP HANA Cloud advisors and automationSAP HANA Cloud advisors and automationSAP HANA Cloud's advisors and the tasks they hand off: the elastic compute node, the partition, index and native storage extension advisors that produce recommendations for performance and efficiency, and SAP Automation Pilot as the service that runs the resulting tasks, which is operations automation on the database. The abstract lists the features and stops there, so what each advisor recommends and how a recommendation becomes an Automation Pilot command is not stated. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Hansika Colomboge Dona, Hui Li, Javier Martin and Roman Belosludtsev, written here from SAP's abstract; the recording is not yet published.
SAP HANA Cloud as a self-managed database: Advisors and automationSAP HANA Cloud as a self-managed database: Advisors and automationSAP HANA Cloud advisors generate recommendations for database administration, aimed at system performance and efficiency, and SAP Automation Pilot runs the manual and administrative tasks around the database as automated processes, which is the operations automation concern on the database side. SAP's abstract names the two services and claims reduced operational overhead; which advisors exist and which tasks the automation covers are not said. A TechEd 2026 session (Wednesday 28 October, Berlin), presented by Javier Martin and Roman Belosludtsev, written here from SAP's abstract; the recording is not yet published.
SAP HANA Cloud as an Esri GeodatabaseSAP HANA Cloud as an Esri GeodatabaseSAP's design for running an Esri ArcGIS Enterprise geodatabase inside SAP HANA Cloud, so that geometries and SAP business data sit in one database and are joined in a HANA calculation view, which is the spatial part of graph, spatial and document data. It traces three personas: an analyst in ArcGIS Pro building query layers over that view, a developer whose CAP application models spatial types such as ST_Point in CDS, and an analyst using a Fiori app on top of such an application. The deployment advice stops at placement: ArcGIS Server and HANA Cloud go in the same region and availability zone, because Esri's certified architectures allow under 5 milliseconds of network latency between them.published 2025-03-25
SAP HANA Cloud as the AI database for SAP Business Data CloudSAP HANA Cloud as the AI database for SAP Business Data CloudSAP HANA Cloud as the AI database at the centre of SAP Business Data Cloud: the strategy behind its AI-first direction, and a Carl Zeiss speaker on how it runs in production today. The abstract names the two products and the customer and no feature, workload or figure, so the edges rest on the products as its subject. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Kush Kashyap and Thomas Hammer, written here from SAP's abstract; the recording is not yet published.
SAP HANA Cloud: The data foundation for contextualizing and reasoningSAP HANA Cloud: The data foundation for contextualizing and reasoningWhere SAP is taking SAP HANA Cloud, described in the abstract as the anchor of SAP's data strategy and a unified layer to store, contextualise and reason across a business, and what that means for a data platform decision. The abstract is a direction statement and names no feature, release or date, so the one edge rests on the product itself. A TechEd 2026 session (Tuesday 27 October, Berlin; also ST106V, virtual), presented by Matthew Zenus and Stefan Baeuerle, written here from SAP's abstract; the recording is not yet published.
Stop guessing, start counting: How generative AI fixed an inventory messStop guessing, start counting: How generative AI fixed an inventory messAn inventory-counting application a business built on SAP Business AI Platform with SAP HANA Cloud and generative AI, to replace recount lists kept by gut feel across SAP ERP Central Component, SAP S/4HANA and Microsoft Excel; the talk promises the app, its architecture and what went wrong. The generative AI part is LLM integration from application code; the abstract names HANA Cloud and generative AI as the two building blocks and says nothing about how either is used. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Ranjeet Kumar, written here from SAP's abstract; the recording is not yet published.
Talking to your database: The new data exploration tools in SAP HANA CloudTalking to your database: The new data exploration tools in SAP HANA CloudSAP HANA Cloud's new data exploration tools take a business question in plain language, find the right database objects and run the query, with no data model and no SQL written beforehand, shown live on a standard business data set. SAP's abstract says the session covers how the tools work, what they need and where they hit their limits, and states none of the three. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Anna Hartmann, written here from SAP's abstract; the recording is not yet published.
Unlock predictive and generative AI with your data in SAP HANA CloudUnlock predictive and generative AI with your data in SAP HANA CloudThe AI features SAP lists for SAP HANA Cloud: the function libraries for tabular prediction and forecasting, where predictive models run inside the database, the vector engine, the knowledge graph engine, which is graph, spatial and document data put to generative use, and SQL to LLM calls. The abstract names the engines and the use cases they are meant for and gives no detail of any one of them. A TechEd 2026 session (Tuesday 27 October, Berlin; also DA204V, virtual), presented by Christoph Morgen and Javier Martin, written here from SAP's abstract; the recording is not yet published.
Use SAP HANA as the Database for a CAP Java ApplicationUse SAP HANA as the Database for a CAP Java ApplicationMoving a CAP Java application off the development database onto HANA, which is the step where the persistence choice stops being invisible.SAP
Agentic memory: Knowledge graph engine and recall in SAP HANA CloudAgentic memory: Knowledge graph engine and recall in SAP HANA CloudThe knowledge graph engine in SAP HANA Cloud as an agent's memory: what the engine, the graph side of graph, spatial and document data, does in an agentic workflow, how an agent keeps what it learns there, the state agent tooling holds between turns, and the SAP AI Core integration through which the database calls LLMs and tabular foundation models such as SAP-RPT-1. The abstract names the engine, the memory role and the AI Core link and does not say how the memory is written or read. DA263 on Wednesday 28 October is a two-hour hands-on on the same engine with a different cast. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Markus Fath and Shraddha Shetty, written here from SAP's abstract; the recording is not yet published.
Build your custom knowledge layer with SAP HANA CloudBuild your custom knowledge layer with SAP HANA CloudSAP HANA Cloud's multi-model engines, the knowledge graph engine among them, as the base for a custom knowledge layer over the enterprise's data, with SAP Business Data Cloud as the product that includes the database. Graph, spatial and document data put to an AI use; the abstract names the graph engine and not the query language or the vector side. A TechEd 2026 session (Wednesday 28 October, Berlin; also ST108V, virtual), presented by Niklas Siemer and Sebastian Schmidt, written here from SAP's abstract; the recording is not yet published.
SAP HANA Cloud as an Esri GeodatabaseSAP HANA Cloud as an Esri GeodatabaseSAP's design for running an Esri ArcGIS Enterprise geodatabase inside SAP HANA Cloud, so that geometries and SAP business data sit in one database and are joined in a HANA calculation view, which is the spatial part of graph, spatial and document data. It traces three personas: an analyst in ArcGIS Pro building query layers over that view, a developer whose CAP application models spatial types such as ST_Point in CDS, and an analyst using a Fiori app on top of such an application. The deployment advice stops at placement: ArcGIS Server and HANA Cloud go in the same region and availability zone, because Esri's certified architectures allow under 5 milliseconds of network latency between them.published 2025-03-25
Unlock predictive and generative AI with your data in SAP HANA CloudUnlock predictive and generative AI with your data in SAP HANA CloudThe AI features SAP lists for SAP HANA Cloud: the function libraries for tabular prediction and forecasting, where predictive models run inside the database, the vector engine, the knowledge graph engine, which is graph, spatial and document data put to generative use, and SQL to LLM calls. The abstract names the engines and the use cases they are meant for and gives no detail of any one of them. A TechEd 2026 session (Tuesday 27 October, Berlin; also DA204V, virtual), presented by Christoph Morgen and Javier Martin, written here from SAP's abstract; the recording is not yet published.
Explore your Hyperscaler data with SAP Business Data CloudExplore your Hyperscaler data with SAP Business Data CloudSAP's map of the ways data held on hyperscaler and partner platforms is joined with SAP data in SAP Business Data Cloud, with a sub-page each for AWS, Azure, Google Cloud, Databricks and Snowflake. It sets four modes side by side: BDC Connect shares data products in both directions over the Delta Sharing protocol from the object store layer, while in the SAP Datasphere layer federation reads remote tables in place, Replication Flows copy SAP data out to stores such as Amazon S3 or Google BigQuery, and Data Flows import files and transform them into Datasphere tables, the last three being the ground loading a warehouse covers. The Snowflake and BigQuery connectors are dated to 2026 releases, and a closing page lists what slows federation, from source and tenant in different regions to queries that do not filter and aggregate at the source.published 2026-05-08
Medallion Reference Architecture for Big Data Processing in SAP HANA CloudMedallion Reference Architecture for Big Data Processing in SAP HANA CloudSAP's medallion layout for SAP HANA Cloud: structured, semi-structured and unstructured data lands raw in HANA Cloud, data lake files as the bronze layer, is cleansed into a common structure in silver, held in data lake files or the HANA database, and is curated and read-optimised in gold, from where it can also be exposed as a Delta Share. The staged path from raw to consumable is the ground loading a warehouse covers, with Spark jobs and SAP Datasphere data flows named as ways to move data between layers and SAP Analytics Cloud among the consumers of gold. It leaves the ingestion method open, to be chosen by source, freshness and performance, and names no pipeline or schedule beyond that.published 2025-04-03
Under the hood of the Delta Sharing protocolUnder the hood of the Delta Sharing protocolHow a Delta Sharing server, dsserv, implements the open-source Delta Sharing protocol for zero-copy sharing: Delta tables ingested, governed and streamed live from local S3-compatible storage into cloud consumers such as Databricks. Neither the server nor the protocol is an atlas entry; the edges are to data federation, the concern zero-copy sharing answers, and to object storage, where the tables sit, and the abstract names no SAP product. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Philipp Nell, written here from SAP's abstract; the recording is not yet published.
Explore SAP Fiori elements for ABAP developersExplore SAP Fiori elements for ABAP developersSAP Fiori elements for an ABAP developer who now builds the UI as well as the RAP business object behind it, the transactional model of ABAP Cloud, in SAP Business Application Studio; the abstract calls the UI side new territory for that developer, and a Fiori elements app is rendered from the service's Fiori annotations rather than hand-written UI code. The abstract names the tool and the stack and does not say which floorplan or annotations are shown. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Björn Schulz, written here from SAP's abstract; the recording is not yet published.
Level up app development: ABAP Cloud model innovations and Joule solutionLevel up app development: ABAP Cloud model innovations and Joule solutionThe ABAP RESTful application programming model, in SAP's abstract, generates multi-node business objects and adds event-driven side effects, collaborative draft, background processing and analytical tables, with the SAP Joule for Developers, ABAP AI capabilities add-on used to speed development up. The generated business objects are the transactional model concern; the abstract names each feature and says nothing about how it is used. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Anne Keller, Carine Tchoutouo Djomo, Frank Jentsch and Marina Blank, written here from SAP's abstract; the recording is not yet published.
Onboard a trading partner from agreement to live monitoringOnboard a trading partner from agreement to live monitoringOne trading partner onboarded from scratch in Trading Partner Management: a trading partner agreement configured, a business document mapped with ML-assisted mapping proposals, which is B2B message mapping, and a transaction run and monitored live, all inside SAP Integration Suite with no EDI tooling outside it. The abstract names the steps and not the document standard or the partner's protocol. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Claudia Carabineiro, Marco Ertel, Marton Luptak and Tobias Griebe, written here from SAP's abstract; the recording is not yet published.
Consume Remote Services in a Full-Stack CAP ApplicationConsume Remote Services in a Full-Stack CAP ApplicationExtending the Developer's Guide application with a remote S/4HANA service — connectivity, importing the Business Partner API, and running against it. SAP publishes this as four separate paths: mock server or real S/4HANA Cloud, times Cloud Foundry or Kyma. One entry covers all four, because the difference between them is which backend and which runtime, not what you learn.SAP
Consume SOAP Web Services in SAP Cloud Application Programming ModelConsume SOAP Web Services in SAP Cloud Application Programming ModelCalling a SOAP service from CAP — the case the remote-service story does not cover, since CAP's own import path speaks OData and OpenAPI.SAP
Extend SAP SuccessFactors on SAP BTP with the SAP Cloud Application Programming ModelExtend SAP SuccessFactors on SAP BTP with the SAP Cloud Application Programming ModelTwelve tutorials, about two hours, building a side-by-side extension of SuccessFactors on BTP. The spine is remote services: importing the SuccessFactors OData service definitions into a CAP model, then treating them as entities the extension reads and writes through, rather than as an API called from a handler. Indexed as one entry because the parts only make sense in order.SAP
Secure Service Consumption Across HyperscalersSecure Service Consumption Across HyperscalersSAP's design for a workload on SAP BTP that calls Amazon Web Services or Google Cloud services with short-lived credentials instead of stored keys, which is the outbound side of authentication: the BTP application proving who it is to another cloud. On AWS it draws two paths, an ID token from Identity Authentication in Cloud Identity Services exchanged through AWS STS for an IAM role, or an X.509 certificate kept in SAP Destination service and presented to IAM Roles Anywhere; on Google Cloud only the token path, through Workload Identity Federation and an impersonated service account. It is drawn for those two hyperscalers only, and Microsoft Azure has no page in it.published 2025-05-14
Use the SAP Cloud SDK in the SAP Cloud Application Programming ModelUse the SAP Cloud SDK in the SAP Cloud Application Programming ModelReaching for the Cloud SDK from inside a CAP service, for the calls CAP's own remote services do not make.SAP
Build real-time event-driven integrations for your enterpriseBuild real-time event-driven integrations for your enterpriseEvent-driven integration with SAP Integration Suite, advanced event mesh inside SAP Integration Suite: where events beat request-response, how publish and subscribe decouple systems, and what a phased move to event-driven integration looks like. Event Mesh as architecture; the abstract names no broker protocol and no CDS mapping. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Daniel Dorst and Karsten Strothmann, written here from SAP's abstract; the recording is not yet published.
Build your own event-driven scenario with advanced event meshBuild your own event-driven scenario with advanced event meshAn event-driven scenario built on SAP Integration Suite, advanced event mesh: queues, topics and subscriptions first, then filtering and event replay, in two parallel tracks, a guided one for newcomers and a second for experienced practitioners. It covers the brokered side of Event Mesh; which systems publish and consume, and which protocol the clients speak, is not stated. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Claudia Carabineiro, Emily Mui, Karsten Strothmann and Tobias Griebe, written here from SAP's abstract; the recording is not yet published.
Designing Event-Driven ApplicationsDesigning Event-Driven ApplicationsSAP's guidance for building applications on event-driven architecture with BTP services. It sets out a two-part strategy: SAP Cloud Application Event Hub for events between SAP cloud applications and BTP, and the SAP Integration Suite family for dedicated event brokers in hybrid landscapes. Its sub-pages then cover EDA patterns, design considerations and AWS and Azure IoT integration. The framing is integration between systems; the in-process outbox and queueing inside one CAP service are not its subject.published 2025-10-10
Modern integration at TÜV Rheinland: APIs, events and cloud transformationModern integration at TÜV Rheinland: APIs, events and cloud transformationTÜV Rheinland's migration from SAP Process Orchestration to SAP Integration Suite with API-led connectivity and event-driven architecture, told through business cases. The abstract names what was used: the SAP Integration Suite, Event Mesh capability, API Management, generative AI for faster development and SAP Cloud ALM for monitoring. It states nothing about how any of them was used, so the edges rest on the names and on the Platform migration the story starts from. A TechEd 2026 session (Wednesday 28 October, Berlin), written here from SAP's abstract; the recording is not yet published.
Unlock composable business using SAP Integration Suite, advanced event meshUnlock composable business using SAP Integration Suite, advanced event meshSAP Integration Suite, advanced event mesh as SAP's product for event-driven, real-time and loosely coupled integration between SAP and third-party systems, which the abstract ties to composable business architecture. The session is about that product and the Event Mesh concern it answers; the abstract states the positioning and no feature, topic or protocol, and a speaker from CCB Management Services is listed without a stated case. A TechEd 2026 session (Tuesday 27 October, Berlin; also IN111V, virtual), presented by Goran D. Stevanovic and Karsten Strothmann, written here from SAP's abstract; the recording is not yet published.
Application to Application IntegrationApplication to Application IntegrationSAP's reference architecture for application-to-application integration, where messages carrying transactional data such as sales orders pass between business applications in near real time and each one triggers the next process step. When the sender's and receiver's APIs do not match, Cloud Integration in SAP Integration Suite sits between them to determine receivers, filter, map structures and convert protocols, which is the ground of integration flows; SAP Connectivity service, Cloud Connector and SAP Destination service reach on-premise receivers, and the edge integration cell runtime keeps processing inside a customer-managed landscape where compliance requires it. Direct exchange without middleware is allowed when the two APIs already align, asynchronous communication is the default the page states, and it is drawn at the level of the pattern, following SAP's Integration Solution Advisory Methodology, without designing any one flow.published 2024-08-01
Build integrations faster with AI-assisted design and operationsBuild integrations faster with AI-assisted design and operationsAI-assisted integration development in SAP Integration Suite: the abstract names embedded generative AI tools that speed up building integrations, agent-ready APIs and event-driven architectures that connect SAP and third-party systems. The Integration Suite edge holds because it is the subject; the Integration flows edge rests on the phrase integration development alone, since the abstract names no tool, no capability area and no feature. A TechEd 2026 session (Wednesday 28 October, Berlin), presented by Finny Babu and Shilpa Vij, written here from SAP's abstract; the recording is not yet published.
Business to Business IntegrationBusiness to Business IntegrationSAP's reference architecture for business-to-business integration, the exchange of business documents with customers, suppliers and other trading partners over agreed standards such as EDIFACT, ANSI X.12 and IDoc and protocols such as AS2. Its design-time steps are Cloud Integration in SAP Integration Suite, the predefined content of SAP Business Accelerator Hub, and Integration Advisor, which defines message implementation and mapping guidelines and generates runtime artifacts from them; Trading Partner Management then turns partner profiles into agreements pushed to the Partner Directory, and generic integration flows on Cloud Integration read those agreements at runtime to exchange messages with each partner. The alternatives it names are API-based exchange where an industry has standardised its APIs, and SAP Business Network with the managed gateway for spend management in place of connecting partners one by one.published 2024-08-01
Connect Business Processes with SAP Master Data IntegrationConnect Business Processes with SAP Master Data IntegrationSAP's reference architecture for keeping master data such as materials, business partners and cost centres consistent across applications with SAP Master Data Integration, a central hub that stores every change in an event log and distributes it to the solutions that consume it. Cloud Integration in SAP Integration Suite carries what the hub does not reach, SAP solutions it does not yet support and third-party or on-premise systems, through an SAP Master Data Integration adapter, which is where the design meets integration flows; newer SAP S/4HANA releases connect to the hub without it. Consolidation, data quality and central governance are outside the architecture and left to SAP Master Data Governance, and SAP Master Data Integration itself has no entry in the atlas yet.published 2024-08-01
Conversational search for the Cloud Integration capabilityConversational search for the Cloud Integration capabilityCloud Integration content becomes searchable in natural language through three architectures SAP's abstract names: MCP servers, retrieval-augmented generation and knowledge graphs, set against the work of analysing and governing a growing SAP Integration Suite tenant. The abstract names the three and does not say which is built or how they compare. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Vadim Klimov, written here from SAP's abstract; the recording is not yet published.
Edge Integration Cell on HyperscalersEdge Integration Cell on HyperscalersSAP's architecture for Edge Integration Cell, the runtime of SAP Integration Suite that executes integration flows in a Kubernetes cluster the customer runs, while design, monitoring and governance stay on SAP BTP and the runtime reaches BTP over outbound-only channels. The main page gives the reasons SAP names for it: data residency, security policies that forbid inbound access, and latency to a distant BTP region. Three sub-pages draw the same setup on AWS, Azure and Google Cloud, each with a private network across three availability zones, a managed Kubernetes cluster, managed PostgreSQL and Redis, sizing left to an SAP Note, and each says it outlines a small production deployment to be treated as a starting point.published 2025-04-18
Evolution of the Code10 CI Accelerator add-on for SAP Integration SuiteEvolution of the Code10 CI Accelerator add-on for SAP Integration SuiteThe Code10 CI Accelerator, a partner add-on that puts a process monitor over pipeline concepts and patterns in Cloud Integration, the Edge Integration Cell runtime and more of SAP Integration Suite, and how it has changed as the suite has. The add-on is not in the atlas, so the edges rest on the Integration Suite capabilities it monitors; the abstract names no pipeline pattern and no feature of the add-on. A TechEd 2026 session (Wednesday 28 October, Berlin), presented by Antonio Valladares Fernandez, written here from SAP's abstract; the recording is not yet published.
Explore version control and automation with GitHub in Cloud IntegrationExplore version control and automation with GitHub in Cloud IntegrationGitHub access set up in Cloud Integration: integration flows committed and versioned from Cloud Integration's own tools, several people working on the same artifacts, and a commit that triggers a CI/CD pipeline. The abstract states what the GitHub connection does and stops before the branch model, the pipeline's steps or which pipeline service runs them. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Marco Ertel, Morten Wittrock, Patrick Kelleher, Shivani Borkar and Tobin Sydneysmith, written here from SAP's abstract; the recording is not yet published.
Governance, automation, and observability in Cloud IntegrationGovernance, automation, and observability in Cloud IntegrationGovernance controls in Cloud Integration for developers and architects, automations written against its public OData API, and monitoring across Cloud Integration and SAP Cloud ALM with AI-assisted error analysis. The abstract names the OData API as the automation surface and does not list the controls or the operations the API exposes. A TechEd 2026 session (Wednesday 28 October, Berlin; also IN208V, virtual), presented by Morten Wittrock and Sunny Kapoor, written here from SAP's abstract; the recording is not yet published.
Rethinking security for modern SAP solution landscapesRethinking security for modern SAP solution landscapesWhere risk goes when clean core moves custom logic out of SAP S/4HANA: into integration flows, CAP extensions, ABAP Cloud code and platform configuration, told through real attack stories, then scanning code, modelling attack paths, adding security gates to CI/CD pipelines and automating safely with Terraform. The scanning edge is to static analysis, the atlas's concern for security findings in ABAP code; the abstract lists the four surfaces and the four practices and describes none of them. A TechEd 2026 session (Wednesday 28 October, Berlin), presented by Tsovinar Chugaszyan, written here from SAP's abstract; the recording is not yet published.
More than 100 trading partners, one platform: Scalable B2B at Algoma SteelMore than 100 trading partners, one platform: Scalable B2B at Algoma SteelB2B integration at Algoma Steel on SAP Integration Suite: more than 100 trading partners served through Trading Partner Management and one generic integration flow architecture, ML-assisted mapping for the documents, and EDI at that scale after a move from SAP Process Integration and SAP Process Orchestration. The abstract names the three pieces, which is the trading partner agreements model, and not the partner standards or the mapping tooling behind them. A TechEd 2026 session (Wednesday 28 October, Berlin), presented by Jagesh Lakdawala and Marco Ertel, written here from SAP's abstract; the recording is not yet published.
Onboard a trading partner from agreement to live monitoringOnboard a trading partner from agreement to live monitoringOne trading partner onboarded from scratch in Trading Partner Management: a trading partner agreement configured, a business document mapped with ML-assisted mapping proposals, which is B2B message mapping, and a transaction run and monitored live, all inside SAP Integration Suite with no EDI tooling outside it. The abstract names the steps and not the document standard or the partner's protocol. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Claudia Carabineiro, Marco Ertel, Marton Luptak and Tobias Griebe, written here from SAP's abstract; the recording is not yet published.
Agent-led custom code migration: From planning to mass adaptationAgent-led custom code migration: From planning to mass adaptationThe Custom Code Migration Agent in SAP Joule for Developers, ABAP AI capabilities, applied to moving custom code from SAP ERP Central Component to SAP Cloud ERP Private: the abstract describes a toolchain that starts with planning in SAP Cloud ALM and ends in mass remediation by the agent, with newer custom code management features shown alongside. Which findings the agent remediates, and how far it goes without a developer, the abstract does not say. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Marco Matha and Olga Dolinskaja, written here from SAP's abstract; the recording is not yet published.
Agentic Engineering for SAP BTP ExtensionsAgentic Engineering for SAP BTP ExtensionsAn agent harness coordinates code generation across isolated Git worktrees, using a skills registry, SAP CAP MCP Server, Fiori MCP Server and UI5 Web Components MCP Server for development context. The diagram shows LiteLLM as a model proxy in front of SAP AI Core, while automated checks and review gate the generated changes. The worked scenario is CAP-based extensions on BTP, with specifications written before generation and reusable skills governed across teams.
AI-assisted full stack development using model context protocol serversAI-assisted full stack development using model context protocol serversMCP servers in Visual Studio Code used to configure, query and change a full-stack application built with CAP, CDS and OData: the agent access to your code concern, a coding assistant reading and changing the project it works in. The abstract names no server, so neither @cap-js/mcp-server nor any other is attached, and it does not say which changes are made. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Sergio Guerrero, written here from SAP's abstract; the recording is not yet published.
Level up app development: ABAP Cloud model innovations and Joule solutionLevel up app development: ABAP Cloud model innovations and Joule solutionThe ABAP RESTful application programming model, in SAP's abstract, generates multi-node business objects and adds event-driven side effects, collaborative draft, background processing and analytical tables, with the SAP Joule for Developers, ABAP AI capabilities add-on used to speed development up. The generated business objects are the transactional model concern; the abstract names each feature and says nothing about how it is used. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Anne Keller, Carine Tchoutouo Djomo, Frank Jentsch and Marina Blank, written here from SAP's abstract; the recording is not yet published.
Migrate and modernize your custom code using RISE with SAP and agentic AIMigrate and modernize your custom code using RISE with SAP and agentic AIThe Custom Code Migration Agent in SAP Joule for Developers, ABAP AI capabilities, shown on the RISE with SAP path that moves custom extensions from SAP ERP Central Component to SAP Cloud ERP Private: the abstract says the agent adapts the code through MCP tools and the AI for ABAP features in the custom code tools, and that the adapted code is then reworked along the clean core approach, the concern ABAP Cloud readiness covers. Which MCP tools, and what the clean core step changes in the code, the abstract leaves open. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Hitesh Bindal, Ingo Braeuninger, Jonas Helin of GitHub, Olga Dolinskaja and Thomas Fiedler, written here from SAP's abstract; the recording is not yet published.
OData to outcomes—Build AI-enabled SAP Fiori apps using SAP Fiori elementsOData to outcomes—Build AI-enabled SAP Fiori apps using SAP Fiori elementsA Fiori elements app built through SAP's MCP servers: the OData V4 service comes from the MCP server for RAP, which the atlas holds as the ADT MCP Server, or from @cap-js/mcp-server for CAP, and the UI from @sap-ux/fiori-mcp-server, with annotations and actions added before the app is tied to SAP's AI features. Agent access to your code on both the service and the UI side; SAP's abstract names the servers and the steps and says nothing about which AI features or which agent host. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Benedikt Schoelch, Sebastian Steinhauer, Sebastian Werner and Stefan Engelhardt, written here from SAP's abstract; the recording is not yet published.
Spec first: The disciplined way to develop ABAP with agentsSpec first: The disciplined way to develop ABAP with agentsSpec-driven ABAP development with a new AWS Toolkit for Eclipse plug-in powered by Kiro, in SAP's words, working inside ABAP Development Tools for Eclipse: SAP's abstract says it reads the codebase, helps with new features, explains legacy code, refactors and generates tests, for S/4HANA modernisation or a new business feature. It answers agent access to your code from inside Eclipse; the plug-in itself is not yet in the atlas, and the abstract does not say how it reaches the ABAP system. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Jon Friesen and Stephan Kremer, written here from SAP's abstract; the recording is not yet published.
Strategy for agent-led development in ABAPStrategy for agent-led development in ABAPSAP Joule for Developers, ABAP AI capabilities moving ABAP development in ADT from AI-assisted to agent-led, across greenfield work and the migration and modernisation of existing solutions: SAP's strategy session for its ABAP AI add-on. The abstract states the direction and names no feature or release date. A TechEd 2026 session (Tuesday 27 October, Berlin; also ST124V, virtual), presented by Alexander Rother and Sonja Lienard, written here from SAP's abstract; the recording is not yet published.
From confident to correct: AI search results you can actually trustFrom confident to correct: AI search results you can actually trustHow SAP LeanIX designs its AI search agents so that a result does not need checking in the UI: agents that adapt to each customer's own workspace model, with ambiguous queries and silent errors at scale as the two problems the talk takes on. The atlas holds no entry for SAP LeanIX itself; the SAP LeanIX MCP Server is the nearest entry, and the abstract names neither it nor any mechanism behind the agents, so the edge rests on the product name alone. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Aviral Vaid and Sai Krishna Subramanian, written here from SAP's abstract; the recording is not yet published.
Model context protocol (MCP) unlocked: Enable governed access to AI agentsModel context protocol (MCP) unlocked: Enable governed access to AI agentsThe MCP Gateway in SAP Integration Suite: the place policy, security and analytics are applied to a curated set of MCP tools before an AI agent reaches enterprise tools and APIs through it, tool governance done in the integration layer and agent access to your systems routed through one gateway. The abstract names the gateway and its three functions and does not say how tools are curated, which policies exist or how the agent authenticates. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Bruno Renzo, Emily Mui, Markus Winter and Sunny Kapoor, written here from SAP's abstract; the recording is not yet published.
SAP Integration Suite as the foundation for enterprise agentic AISAP Integration Suite as the foundation for enterprise agentic AISAP Integration Suite as the way an agent reaches systems: SAP's abstract says it gives agents governed access to APIs, events, applications, trading partners and processes across SAP and third-party landscapes, with AI assistance in the design, deployment and operation of the integrations. That is agent access to your systems through middleware; the abstract names no protocol and no gateway. A TechEd 2026 session (Tuesday 27 October, Berlin; also ST104V, virtual), presented by Markus Winter and Udo Paltzer, written here from SAP's abstract; the recording is not yet published.
Speed up your cloud journey with agentic data management and configurationSpeed up your cloud journey with agentic data management and configurationThe Configuration Assistant for SAP Cloud ERP: an agent that validates insights from an organisation's data and maps toward a target business configuration, under the heading of agentic data management, with data preparation, transparency and governance as the stated aims. The atlas holds no entry for the Configuration Assistant and no concern for business configuration of an ERP, so the edge is to Agent access to your systems, the nearest concern, an agent working on a system's data and configuration; the abstract's configuration is not the per-environment application settings the atlas files under that word. The abstract states aims and no feature detail. A TechEd 2026 session (Wednesday 28 October, Berlin; the same abstract runs as the hands-on TM267), presented by Felix Peter and Helen Sontowski, written here from SAP's abstract; the recording is not yet published.
Agentic Engineering for SAP BTP ExtensionsAgentic Engineering for SAP BTP ExtensionsAn agent harness coordinates code generation across isolated Git worktrees, using a skills registry, SAP CAP MCP Server, Fiori MCP Server and UI5 Web Components MCP Server for development context. The diagram shows LiteLLM as a model proxy in front of SAP AI Core, while automated checks and review gate the generated changes. The worked scenario is CAP-based extensions on BTP, with specifications written before generation and reusable skills governed across teams.
Agentic AI & AI AgentsAgentic AI & AI AgentsSAP's target picture for AI agents: Joule as the engagement layer — Joule Work, Joule Assistants, Joule Agents — with custom agents from customers, partners and SAP teams connecting through A2A for agent-to-agent collaboration and MCP for tool connectivity, on the SAP Business AI Platform. It says up front that parts are not generally available yet, in particular bidirectional communication with third-party agents through the Agent Gateway, so it reads as direction with the building blocks named rather than a design to copy today.published 2026-08-27
Agentic memory: Knowledge graph engine and recall in SAP HANA CloudAgentic memory: Knowledge graph engine and recall in SAP HANA CloudThe knowledge graph engine in SAP HANA Cloud as an agent's memory: what the engine, the graph side of graph, spatial and document data, does in an agentic workflow, how an agent keeps what it learns there, the state agent tooling holds between turns, and the SAP AI Core integration through which the database calls LLMs and tabular foundation models such as SAP-RPT-1. The abstract names the engine, the memory role and the AI Core link and does not say how the memory is written or read. DA263 on Wednesday 28 October is a two-hour hands-on on the same engine with a different cast. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Markus Fath and Shraddha Shetty, written here from SAP's abstract; the recording is not yet published.
AI-enhanced analytics with SAP Business AI PlatformAI-enhanced analytics with SAP Business AI PlatformSAP Business Data Cloud data products joined to an ontology, a semantic layer the abstract says is supported by the Model Context Protocol, and read from Joule Work (SAP Joule) and SAP Analytics Cloud: that is the architecture SAP's abstract states for its AI-enabled analytics. The abstract names the parts and not how the semantic layer is modelled or what an analytics developer builds against. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Hacen Benkhedah, Joaquin Recio Huertas, Matilda Hyka and Oliver Huth, written here from SAP's abstract; the recording is not yet published.
AI-native North Star architecture — Platform LayerAI-native North Star architecture — Platform LayerThe platform layer of SAP's North Star architecture, the chapter that says where agents run and what a developer builds them with. It names an AI Golden Path built on the SAP Cloud Application Programming Model, the ABAP Cloud development model with RAP and the SAP Fiori design system, and a managed agent runtime on SAP BTP that is designed to provide software development kits for building agents in any framework, an agent sandbox, container-hosted execution, a skills registry and continuous evaluations, which is the ground agent tooling covers. Agents are extended without changing their code through four patterns, the first of them tool extensibility through the Model Context Protocol, the concern MCP servers is named for; the process-layer chapter adds that a pro-code path with a standardised agent SDK and a prompt-driven path through the Joule Studio solution produce the same code artifact on the same runtime. It describes a design SAP intends rather than products that exist, and the SDK and the registry it names have no entry here yet.published 2026-05-13
AI-native North Star architecture — Platform Layer
Agent tooling changed in @cap-js/agents 0.9.1, 2026-08-14. Affects A reference.
Build your first agent with Joule Studio in a pro-code wayBuild your first agent with Joule Studio in a pro-code wayThe command line interface of Joule Studio, which the atlas holds as @sap/joule-work-dev-cli-early-adopters, carries an agent from a structured intent through generated product requirements documentation and wired APIs to a deployment on Joule Studio's SAP-managed runtime, in one guided flow. SAP's abstract names the stages of that pipeline and promises working code at the end; what the generated requirements and APIs look like is not described. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Charan Ravikumar, Evgenii Skrebtcov, Maria Kondratyeva and Simon Endres, written here from SAP's abstract; the recording is not yet published.
Connecting AI agents to the ABAP RESTful application programming modelConnecting AI agents to the ABAP RESTful application programming modelJoule Studio, classic edition connects Joule Agents to applications built with the ABAP RESTful application programming model through actions and skills, calling the OData services those applications expose their business objects through: the tools an agent may call, which is the agent tooling concern seen from the ABAP side. The abstract promises alternative integration patterns and does not name them. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Leon Karlau, written here from SAP's abstract; the recording is not yet published.
Deploy, review, break, fix: Govern cloud transports with agility and AIDeploy, review, break, fix: Govern cloud transports with agility and AIFive BTP services in one delivery chain, as the abstract lays it out: a transport is triggered in SAP Content Agent Service, tested in SAP Cloud Transport Management, its failure is raised by SAP Alert Notification service for SAP BTP and remediated by a SAP Joule agent with SAP Automation Pilot, and SAP Cloud Logging keeps the history for root-cause analysis. The chain from alert to remediation is the operations automation concern; what the Joule agent decides on its own is not in the abstract. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Biser Simeonov, Daniel Funkert, Sven Rullmann and Thorsten Sandfuchs, written here from SAP's abstract; the recording is not yet published.
Discover fast-track implementation of SAP Cloud ERP with AIDiscover fast-track implementation of SAP Cloud ERP with AISAP's implementation practice for SAP S/4HANA Cloud Public Edition and the AI-driven tooling SAP says is changing stages of a project, with faster and more predictable deployments, less manual effort and lower risk as the stated outcomes. The abstract names the product, an external here, and no tool; the edge is to SAP Joule because SAP's AI tooling for implementation in the sibling sessions TM109, TM263 and TM265 is Joule for Consultants, and whether this session shows it is not stated. A TechEd 2026 session (Wednesday 28 October, Berlin), presented by Anurag Barua and Khaled MUSILHY, written here from SAP's abstract; the recording is not yet published.
Discover how SAP Joule for Consultants transforms cloud implementationsDiscover how SAP Joule for Consultants transforms cloud implementationsA customer's use of SAP Joule for Consultants in a cloud transformation: grounding project data, running fit-to-standard workshops faster and keeping teams aligned, followed by the technical architecture behind those capabilities and an early road map preview on feasibility for developers and enterprise architects. The edge is to SAP Joule, of which Joule for Consultants is the offering for consultants and has no entry of its own here; the abstract leaves the customer as a placeholder and the architecture to the session. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Philipp Kandziora and Yi Hsuan Lin, written here from SAP's abstract; the recording is not yet published.
From intent to extension: Joule and the future of solution extensibilityFrom intent to extension: Joule and the future of solution extensibilityHow Joule turns natural-language intent into extensions across SAP Autonomous Suite: intent-based agent extensions, enriching the agents SAP delivers, packaging options for partners and what SAP calls a harmonised extensibility experience. The edges are to SAP Joule, which does the translating, and to Extensibility, the concern; the abstract names the directions and no feature that ships today. A TechEd 2026 session (Wednesday 28 October, Berlin), presented by Amitha Kamath, Oren Shatil and Richard Kuba, written here from SAP's abstract; the recording is not yet published.
Get to know our AI-enhanced mobile apps across the Autonomous EnterpriseGet to know our AI-enhanced mobile apps across the Autonomous EnterpriseA demo of the Joule Work mobile app, part of SAP Joule, and selected SAP mobile apps, showing the mobile AI features meant for using SAP Autonomous Suite on the go, followed by the mobile AI patterns and how to build your own Mobile apps with SAP Business AI Platform. The abstract names the apps and the patterns and states no feature or tool, so what building your own involves is not said. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Sandeep Tetali and Thilo Berndt, written here from SAP's abstract; the recording is not yet published.
Inside Joule Studio runtime: Agent deployment and integrationsInside Joule Studio runtime: Agent deployment and integrationsJoule Studio runtime from the inside: the tools and services SAP manages to deploy, integrate, run, extend and operate agents at scale, and the integrations through the agent gateway and SAP S/4HANA Cloud Private Edition. The edge is to SAP Joule, whose agents the runtime runs; the atlas reaches that runtime through @sap/joule-work-dev-cli-early-adopters, which deploys a solution to it, and the abstract names neither the CLI nor a service by name. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Andre Lamego and Jens Huesken, written here from SAP's abstract; the recording is not yet published.
Integrating and Extending JouleIntegrating and Extending JouleSAP's reference architecture for SAP Joule across SAP cloud applications: a request is checked against a Scenario Catalog of the applications' skills and a Knowledge Catalog answered by retrieval-augmented generation, combined with the user's roles and history, sent to an LLM available through the generative AI hub, and, where a Joule function is needed, turned into a call to the backend. Its identity page is the authentication path: each user sits in the Identity Directory of Cloud Identity Services with a Global User ID, Identity Provisioning synchronises role assignments into SAP Build Work Zone, whose navigation service decides which functions a user may call, and the Destination service exchanges the user's token to call a function in the user's name. Its extension page covers Joule Studio in SAP Build, where Joule skills automate rule-based tasks over APIs and AI agents plan and reason with models and document grounding from SAP AI Core, the ground agent tooling covers; a later Joule Studio page describes a managed Joule Studio Runtime on the SAP Business AI Platform, which has no entry here.published 2026-03-16
Joule and related AI offerings from SAP: One platform, many systemsJoule and related AI offerings from SAP: One platform, many systemsSAP Joule run across dozens of SAP systems: the SAP for Me portal, orchestration across systems, configuration and credential management, monitoring and tenant isolation are the topics SAP's abstract lists. It stays on the operating side and says nothing about building on Joule. A TechEd 2026 session (Wednesday 28 October, Berlin; also JW301V, virtual), presented by Lukas Lochner, Marvin Klaus and Mathias Rup, written here from SAP's abstract; the recording is not yet published.
Joule and SAP Knowledge Graph: Context-aware AI across SAP solutionsJoule and SAP Knowledge Graph: Context-aware AI across SAP solutionsThe catalogue carries RA107's abstract under this title, and what it describes is SAP AI Core as the management and orchestration layer of an AI architecture: extending Joule Agents in SAP Joule, the model library in Joule Studio for contextual reasoning, connecting data products from SAP Business Data Cloud, and embedding AI in SAP S/4HANA. The SAP Knowledge Graph the title names does not appear in that text, so the edges rest on the abstract as published, and whether the session follows the title or the abstract is not known until it is recorded. A TechEd 2026 session (Wednesday 28 October, Berlin; also RA110V, virtual), presented by Jan Portisch and Pavithra G K, written here from SAP's abstract; the recording is not yet published.
Joule without walls: From personal skills to enterprise interoperabilityJoule without walls: From personal skills to enterprise interoperabilitySAP Joule connects outward over two protocols, A2A and MCP, which SAP's abstract names as the foundation of its open ecosystem, with Joule Assistants as composable agents and extensibility built in. The session draws the line between a personal extension of Joule and one that needs enterprise governance; the abstract does not say where that line falls. A TechEd 2026 session (Wednesday 28 October, Berlin), presented by Mathis Boerner and Thomas Mueller, written here from SAP's abstract; the recording is not yet published.
SAP’s compositional design system: Craft enterprise UIs with AI on the flySAP’s compositional design system: Craft enterprise UIs with AI on the flySAP's compositional design system is the engine behind the generated interface in Joule Work, the front of SAP Joule: SAP's abstract says AI assembles the UI at runtime from primitives and composites under a body of design knowledge, inside a brand-safe design system, and that the session covers the architecture that keeps the result consistent. A third shape of Generative UI beside the two the capability describes, since here the model composes the interface at runtime. A TechEd 2026 session (Wednesday 28 October, Berlin), presented by Philip Miseldine and Sophia Levens, written here from SAP's abstract; the recording is not yet published.
The road map for SAP Joule for Consultants—your go-to SAP consulting toolThe road map for SAP Joule for Consultants—your go-to SAP consulting toolSAP's road map for SAP Joule for Consultants, which the abstract describes as becoming the tool for SAP software projects: landscape awareness and secure system connectivity, so that Joule understands an organisation's SAP environments and gives project teams more contextual guidance. The atlas holds no entry for Joule for Consultants, so the piece enters on SAP Joule, the product it is an edition of; the abstract states outcomes and no feature or date. A TechEd 2026 session (Wednesday 28 October, Berlin), presented by Natalie Han and Sachin Kaura, written here from SAP's abstract; the recording is not yet published.
What’s next for agentic analytics and planning in SAP Business Data CloudWhat’s next for agentic analytics and planning in SAP Business Data CloudWhat is next for agentic analytics and planning in SAP Business Data Cloud: SAP Joule's agents automating insight delivery, analysis, narrative generation and modelling tasks. A road map session; the abstract names the four kinds of task and no agent or date. A TechEd 2026 session (Tuesday 27 October, Berlin; also DA806V, virtual), presented by Kristian Ruemmelin, written here from SAP's abstract; the recording is not yet published.
What’s next for the core platform capabilities of SAP Business AI PlatformWhat’s next for the core platform capabilities of SAP Business AI PlatformA preview of the operations layer beneath SAP Business AI Platform: selected road map highlights across Joule Studio runtime, Cloud Identity Services and SAP Cloud Logging, on how enterprise AI is governed and run. The edges are to the two named services and to SAP Joule, whose agents the Joule Studio runtime runs; the abstract names the three areas and no highlight. A TechEd 2026 session (Tuesday 27 October, Berlin; also XP825V, virtual), presented by Andre Lamego and Jens Huesken, written here from SAP's abstract; the recording is not yet published.
Zero token architecture for Joule AgentsZero token architecture for Joule AgentsA pattern for SAP Joule's agents in which an agent maps the solution path once, solves the problem, generates reusable code or configuration and validates it, and later requests reuse that output, so discovery is done by the model and execution is repeatable. The abstract states the pattern as an idea and names no Joule component and no case it was tried on. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by EDGAR ADRIAN MARTINEZ ARCE, written here from SAP's abstract; the recording is not yet published.
Behind the Autonomous Enterprise: SAP Knowledge Graph and SAP Domain ModelsBehind the Autonomous Enterprise: SAP Knowledge Graph and SAP Domain ModelsThe strategy behind SAP Business AI's intelligence layer: SAP Knowledge Graph for enterprise context, SAP Domain Models for SAP-specific expertise and tabular AI for predictions, unified on SAP AI Core with SAP Document AI. Knowledge Graph and Domain Models are not atlas entries, so the edges rest on the two products the abstract names as the infrastructure and on Predictive models for the tabular AI; nothing is stated about what any of them does in the layer. A TechEd 2026 session (Tuesday 27 October, Berlin; also ST103V, virtual), presented by Jan Portisch and Richard Grandpierre, written here from SAP's abstract; the recording is not yet published.
How SAP Document AI brings agentic intelligence to business documentsHow SAP Document AI brings agentic intelligence to business documentsSAP Document AI as SAP's abstract now describes it: composable, agent-ready skills for schemaless extraction, classification and summarisation of business documents, so Joule Agents can read and act on unstructured content, plus new document foundation models and agentic validation in its workflow engine. That widens document extraction past the fixed-schema fields the atlas entry records; the abstract names the features and not their release state. A TechEd 2026 session (Wednesday 28 October, Berlin), presented by Dheeraj Diwan, Soeren Leibach and Tomasz Janasz, written here from SAP's abstract; the recording is not yet published.
SAP Document AISAP Document AISAP's reference architecture for SAP Document AI, first as SAP composes the service on BTP for document extraction: OCR, pretrained models, customer-defined schemas and LLM calls through SAP AI Core and its Prompt Registry in one pipeline, with tenant-isolated persistence in SAP HANA Cloud, PostgreSQL and an object store. Its scenario pages then lay out a solution in three layers: intake through Outlook and SharePoint inbound channels, the workspace UI, the Joule Work mobile app or the upload API; classification and extraction with a confidence score per field, automatic confirmation above a threshold and review of the rest in the workspace; and posting through outbound channels, directly to a REST API, through an SAP Integration Suite flow, or through a CAP service that maps the fields and calls SAP S/4HANA over OData. Enrichment beyond the service's own master data lookup is left to a CAP application or an Integration Suite flow triggered from an outbound channel, and direct API posting leaves error handling, retries and monitoring to the application.published 2026-06-03
SAP’s compositional design system: Craft enterprise UIs with AI on the flySAP’s compositional design system: Craft enterprise UIs with AI on the flySAP's compositional design system is the engine behind the generated interface in Joule Work, the front of SAP Joule: SAP's abstract says AI assembles the UI at runtime from primitives and composites under a body of design knowledge, inside a brand-safe design system, and that the session covers the architecture that keeps the result consistent. A third shape of Generative UI beside the two the capability describes, since here the model composes the interface at runtime. A TechEd 2026 session (Wednesday 28 October, Berlin), presented by Philip Miseldine and Sophia Levens, written here from SAP's abstract; the recording is not yet published.
Agentic memory: Knowledge graph engine and recall in SAP HANA CloudAgentic memory: Knowledge graph engine and recall in SAP HANA CloudThe knowledge graph engine in SAP HANA Cloud as an agent's memory: what the engine, the graph side of graph, spatial and document data, does in an agentic workflow, how an agent keeps what it learns there, the state agent tooling holds between turns, and the SAP AI Core integration through which the database calls LLMs and tabular foundation models such as SAP-RPT-1. The abstract names the engine, the memory role and the AI Core link and does not say how the memory is written or read. DA263 on Wednesday 28 October is a two-hour hands-on on the same engine with a different cast. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Markus Fath and Shraddha Shetty, written here from SAP's abstract; the recording is not yet published.
AI-enabled administration: Automating log analysis with generative AI hubAI-enabled administration: Automating log analysis with generative AI hubA log analysis tool for incident work, built in SAP Business Application Studio with the generative AI hub feature, which SAP AI Core ships as its LLM integration by its own documentation: it automates root-cause analysis over system errors and masks sensitive data. SAP's abstract states the tool's jobs and not how the hub is called, what the masking covers or which model answers. A TechEd 2026 session (Wednesday 28 October, Berlin), with no speaker listed in the catalogue at the time of writing, written here from SAP's abstract; the recording is not yet published.
Behind the Autonomous Enterprise: SAP Knowledge Graph and SAP Domain ModelsBehind the Autonomous Enterprise: SAP Knowledge Graph and SAP Domain ModelsThe strategy behind SAP Business AI's intelligence layer: SAP Knowledge Graph for enterprise context, SAP Domain Models for SAP-specific expertise and tabular AI for predictions, unified on SAP AI Core with SAP Document AI. Knowledge Graph and Domain Models are not atlas entries, so the edges rest on the two products the abstract names as the infrastructure and on Predictive models for the tabular AI; nothing is stated about what any of them does in the layer. A TechEd 2026 session (Tuesday 27 October, Berlin; also ST103V, virtual), presented by Jan Portisch and Richard Grandpierre, written here from SAP's abstract; the recording is not yet published.
Build AI agents and applications natively on SAP HANA CloudBuild AI agents and applications natively on SAP HANA CloudSAP HANA Cloud as the base for agentic applications on SAP Business AI Platform: the session goes through CAP, the SAP HANA Cloud vector engine and SAP AI Core, with architecture patterns and lessons learned from building AI-supported applications. SAP's abstract names the three parts of that stack and the vector engine as the database's feature in it, and describes none of the patterns. A TechEd 2026 session (Wednesday 28 October, Berlin; also DA113V, virtual), presented by Christoph Morgen and Shraddha Shetty, written here from SAP's abstract; the recording is not yet published.
Build business differentiation with SAP AI CoreBuild business differentiation with SAP AI CoreSAP AI Core as the orchestration layer for enterprise AI, worked through with SAP's engineers: extend Joule Agents with models from its library, ground them in SAP Business Data Cloud products, embed them in SAP S/4HANA flows, then govern, scale and monitor them from prototype to production. The abstract says what the layer does for an agent and not which services carry each step. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by David Knaack, Franziska Dobrigkeit, Hadi Hares and Jonas Israel, written here from SAP's abstract; the recording is not yet published.
Enriching AI models with SAP AI Core in SAP Business Data CloudEnriching AI models with SAP AI Core in SAP Business Data CloudThe integration between SAP Business Data Cloud and SAP AI Core, through which data products with their semantics feed AI models for benchmarking, custom AI development and agentic analytics and applications. The abstract names the two products and the three uses and states nothing about how the data reaches AI Core or what the integration consists of. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by San Tran and Sandy Tran, written here from SAP's abstract; the recording is not yet published.
Generative AI on SAP BTPGenerative AI on SAP BTPThe reference shape for a generative AI application on BTP: a CAP backend, SAP HANA Cloud holding data and embeddings for similarity search through its vector engine, and the Generative AI Hub in SAP AI Core as the single access point to foundation models. It shows retrieval-augmented generation on that stack and names the CAP plugins and SDKs that connect the pieces, for both Cloud Foundry and Kyma.published 2025-09-02
Generative AI on SAP BTP
LLM integration changed in @cap-js/ai 1.0.0, 2026-04-28. Affects A reference.
Joule and SAP Knowledge Graph: Context-aware AI across SAP solutionsJoule and SAP Knowledge Graph: Context-aware AI across SAP solutionsThe catalogue carries RA107's abstract under this title, and what it describes is SAP AI Core as the management and orchestration layer of an AI architecture: extending Joule Agents in SAP Joule, the model library in Joule Studio for contextual reasoning, connecting data products from SAP Business Data Cloud, and embedding AI in SAP S/4HANA. The SAP Knowledge Graph the title names does not appear in that text, so the edges rest on the abstract as published, and whether the session follows the title or the abstract is not known until it is recorded. A TechEd 2026 session (Wednesday 28 October, Berlin; also RA110V, virtual), presented by Jan Portisch and Pavithra G K, written here from SAP's abstract; the recording is not yet published.
SAP AI Core deep dive: Models, agents, and business context at scaleSAP AI Core deep dive: Models, agents, and business context at scaleSAP AI Core read as the management and orchestration layer of an AI architecture, beyond the model runtime: SAP's abstract lists extending Joule Agents, the model library in Joule Studio for contextual reasoning, connecting data products from SAP Business Data Cloud, and embedding AI in SAP S/4HANA. It names the connections and not the APIs behind them. A TechEd 2026 session (Tuesday 27 October, Berlin; also RA107V, virtual), presented by Franziska Dobrigkeit and Hadi Hares, written here from SAP's abstract; the recording is not yet published.
Ship your own sandboxed AI operations agent to Kyma in two hoursShip your own sandboxed AI operations agent to Kyma in two hoursAn operations agent built and then broken on purpose: the abstract has participants deploy a reasoning agent to SAP BTP, Kyma runtime, connect it to SAP AI Core, give it observability over the runtime and cause a failure for it to diagnose, the operations automation concern with an agent doing the diagnosis. Patterns for cost control and monitoring are promised at the end; the agent framework and how the sandbox is drawn are not named. A TechEd 2026 session (Tuesday 27 October, Berlin, two hours), presented by Christian Lechner, Piotr Tesny, Thorsten Sandfuchs and Vipin VijayKumar, written here from SAP's abstract; the recording is not yet published.
Stop guessing, start counting: How generative AI fixed an inventory messStop guessing, start counting: How generative AI fixed an inventory messAn inventory-counting application a business built on SAP Business AI Platform with SAP HANA Cloud and generative AI, to replace recount lists kept by gut feel across SAP ERP Central Component, SAP S/4HANA and Microsoft Excel; the talk promises the app, its architecture and what went wrong. The generative AI part is LLM integration from application code; the abstract names HANA Cloud and generative AI as the two building blocks and says nothing about how either is used. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Ranjeet Kumar, written here from SAP's abstract; the recording is not yet published.
Behind the Autonomous Enterprise: SAP Knowledge Graph and SAP Domain ModelsBehind the Autonomous Enterprise: SAP Knowledge Graph and SAP Domain ModelsThe strategy behind SAP Business AI's intelligence layer: SAP Knowledge Graph for enterprise context, SAP Domain Models for SAP-specific expertise and tabular AI for predictions, unified on SAP AI Core with SAP Document AI. Knowledge Graph and Domain Models are not atlas entries, so the edges rest on the two products the abstract names as the infrastructure and on Predictive models for the tabular AI; nothing is stated about what any of them does in the layer. A TechEd 2026 session (Tuesday 27 October, Berlin; also ST103V, virtual), presented by Jan Portisch and Richard Grandpierre, written here from SAP's abstract; the recording is not yet published.
Federated Machine Learning with SAP DatasphereFederated Machine Learning with SAP DatasphereSAP's design for training predictive models on an external machine learning platform against SAP Datasphere data that is not replicated to that platform. The open-source FedML Python library runs in the platform's notebook, connects to Datasphere over Python/SQLDBC and reads the analytic models in which Datasphere unifies SAP and non-SAP sources; a trained model can then be deployed to SAP AI Core, or in several sub-pages to SAP BTP, Kyma runtime, which is the predictive models path where training happens outside SAP. Sub-pages cover Amazon SageMaker, Azure Machine Learning, Google Vertex AI, Databricks, NVIDIA RAPIDS on GPUs and IBM watsonx.published 2025-01-23
Transforming Enterprise Data Strategy with SAP Business Data CloudTransforming Enterprise Data Strategy with SAP Business Data CloudSAP's layered picture of SAP Business Data Cloud, from lake storage and compute up to a knowledge core and agents, with eight sub-pages that each work one part through. The data products page is the cataloguing and lineage part: datasets described by Open Resource Discovery metadata, listed in the BDC catalog and shared over Delta Sharing to SAP Databricks and SAP HANA Cloud, with SAP Datasphere as a consumer on the intelligent content page; other pages install intelligent content, bring SAP BW data in through the Data Product Generator, provision groups by SCIM from Cloud Identity Services into SAP Databricks, which is identity provisioning, and train predictive models in SAP Databricks that SAP AI Core then serves for batch and real-time scoring. The main page states direction more than mechanism, and the BW page marks SQL Share for derived and OData for analytical data products as to be available.published 2026-05-12
Unlock predictive and generative AI with your data in SAP HANA CloudUnlock predictive and generative AI with your data in SAP HANA CloudThe AI features SAP lists for SAP HANA Cloud: the function libraries for tabular prediction and forecasting, where predictive models run inside the database, the vector engine, the knowledge graph engine, which is graph, spatial and document data put to generative use, and SQL to LLM calls. The abstract names the engines and the use cases they are meant for and gives no detail of any one of them. A TechEd 2026 session (Tuesday 27 October, Berlin; also DA204V, virtual), presented by Christoph Morgen and Javier Martin, written here from SAP's abstract; the recording is not yet published.
Conversational search for the Cloud Integration capabilityConversational search for the Cloud Integration capabilityCloud Integration content becomes searchable in natural language through three architectures SAP's abstract names: MCP servers, retrieval-augmented generation and knowledge graphs, set against the work of analysing and governing a growing SAP Integration Suite tenant. The abstract names the three and does not say which is built or how they compare. A TechEd 2026 session (Tuesday 27 October, Berlin), presented by Vadim Klimov, written here from SAP's abstract; the recording is not yet published.
Generative AI on SAP BTPGenerative AI on SAP BTPThe reference shape for a generative AI application on BTP: a CAP backend, SAP HANA Cloud holding data and embeddings for similarity search through its vector engine, and the Generative AI Hub in SAP AI Core as the single access point to foundation models. It shows retrieval-augmented generation on that stack and names the CAP plugins and SDKs that connect the pieces, for both Cloud Foundry and Kyma.published 2025-09-02
Generative AI on SAP BTP
LLM integration changed in @cap-js/ai 1.0.0, 2026-04-28. Affects A reference.