BrowseSAP Business Technology Platform, also named SAP Business AI Platform
Everything in BTP/BAIP
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Domain: AI & Agents
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Agent access to your codeSAP and community
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.
Agent access to your systemsSAP and community
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.
MCP Gateway in Practice: Architecture, configuration, and hands-onMCP Gateway in Practice: Architecture, configuration, and hands-onA Devtoberfest 2026 integration-track session (INT-21) on the MCP gateway of SAP Integration Suite: curated enterprise APIs served to agents as MCP tools over JSON-RPC, behind the authentication, authorization and traffic policies an API artifact already carries, with the existing API layer left in place. The hands-on half composes S/4HANA plant, material-stock and supplier data with a non-SAP location-risk source into one business data graph, downloads its OpenAPI specification, creates an MCP server artifact with tools, prompts and a surge-protection policy over that endpoint, and publishes it as a product in Developer Hub of API Management, where an agent developer subscribes and gets OAuth credentials. An MCP client then asks for 15 brake pads and ranks plants by stock, location risk and distance from Walldorf, which is what the agent access to your systems edge rests on; the Q&A covers principal propagation to the backend, how errors reach the model, and which Integration Suite editions carry the gateway.SAP Developers
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.
Agent guidanceSAP and community
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.
Agent toolingSAP only
Agent-led test management: Hands-on lab with Joule in SAP Cloud ALMAgent-led test management: Hands-on lab with Joule in SAP Cloud ALMThe Test Management Assistant, a Joule capability in SAP Cloud ALM, worked through on project scenarios: scoping requirements, detecting coverage gaps and generating test cases with AI. The edge is to SAP Joule, which the assistant runs on; SAP Cloud ALM has no entry here, and the atlas's testing concern, proving a service's model and handlers, is not this session's test management. A TechEd 2026 hands-on session (Wednesday 28 October, Berlin), presented by Christina Pickhardt, Daniel Lorenz, Niclas Weidner and Tobias Keller, 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-accelerated RISE with SAP migration with the system transition workbenchAI-accelerated RISE with SAP migration with the system transition workbenchSAP Joule for Consultants and the RISE with SAP system transition workbench in a move to SAP S/4HANA Cloud Private Edition: readiness assessments, migration workflows and the SAP tools involved. The edge is to SAP Joule, of which Joule for Consultants is a part; the system transition workbench has no entry here, and Platform migration covers applications leaving older BTP platforms, not an ERP system's move. A TechEd 2026 hands-on session (Wednesday 28 October, Berlin), presented by Daniel Funkert, Kristin Aleksandrova, Mirja Kempin and Moritz Gysler, 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.
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.
Building agentic applications with SAP HANA CloudBuilding agentic applications with SAP HANA CloudA CAP application extended with semantic search and agent features on top of SAP HANA Cloud's vector engine and SAP AI Core, built in a hands-on workshop. The abstract names the parts, CAP, the vector engine and AI Core, and the two additions: semantic search, the retrieval half of retrieval-augmented generation, and LLM-supported agent capabilities inside the application, which is agent tooling. Which embedding model, which CAP runtime and how the agent calls its tools are not stated. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Hui Li, Ritty Joseph, Shraddha Shetty and Tanuja Jadhav, written here from SAP's abstract; the recording is not yet published.
Building custom Joule Agents with SAP Knowledge GraphBuilding custom Joule Agents with SAP Knowledge GraphCustom Joule Agents built in a hands-on with SAP Knowledge Graph and Joule Studio: discovering APIs from a user's intent, grounding an agent's answers in business context, and integrating data products for SAP Business Data Cloud. The agents are SAP Joule's; the Knowledge Graph is not an atlas entry, and the abstract does not say which Joule Studio edition the exercises use. A TechEd 2026 hands-on session (Wednesday 28 October, Berlin), presented by Jan Portisch, Lucas Kiesow, Pavithra G K and Rafael Martin, written here from SAP's abstract; no recording is announced.
Building enterprise agent extensions with the Joule Studio solutionBuilding enterprise agent extensions with the Joule Studio solutionExtending SAP's standard agents with third-party integrations and business actions in Joule Studio: agents that run a process across systems, call an external service, put an approval step in the middle and bring the result back into the business context, which is what SAP Joule's agents do and what Joule Studio, classic edition is in the atlas. The abstract names Joule Studio without saying which edition the exercise uses, and lists outcomes rather than the steps built. A TechEd 2026 hands-on session (Wednesday 28 October, Berlin), presented by Charan Ravikumar, Jacob Hornberger, Maria Kondratyeva and Michael Zadikowitsch, 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.
Content-based Agents with SAP Joule Studio Agent BuilderContent-based Agents with SAP Joule Studio Agent BuilderJoule Studio, classic edition, the capability in SAP Build the page calls Joule Studio, is where an organisation creates and manages its own Joule skills and Joule agents; its Agent Builder is for a custom agent that handles a multi-step task by combining instructions, model-backed planning and reasoning, and a configured set of tools, Joule skills, document resources, MCP servers, or other agents run as subagents. The page states an agent executes inside the calling user's own security context through SAP Cloud Identity Services, and can be tried against a test conversation before deployment. That is the tool-and-turn-taking ground agent tooling covers, here built through Joule Studio rather than in application code.
Custom Joule SkillsCustom Joule SkillsA custom Joule skill is a workflow written to extend what Joule does out of the box for one specific business need, built and deployed through Joule Studio in SAP Build; the page states this is the supported way to extend Joule's built-in capabilities. Through Joule Studio a skill reaches SAP and external APIs via the destinations already configured in the BTP subaccount and Build environment, with the workflow itself versioned, monitored and deployable from the same tool.
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.
Experience core foundational capabilities of SAP Cloud ERPExperience core foundational capabilities of SAP Cloud ERPGuided exercises in SAP S/4HANA Cloud Public Edition, which SAP calls the execution backbone of the Autonomous Enterprise: validating AI capabilities against master data for industry and domain needs, generating AI-driven KPIs and reporting summaries. The product is an external here and the abstract names no AI feature by name; the edge is to SAP Joule, SAP's AI layer across its applications and the one entry the AI capabilities of SAP Cloud ERP attach to, which the abstract itself does not name. A TechEd 2026 hands-on session (Wednesday 28 October, Berlin), presented by Akshat Kharial, Ankush Thareja and Nises Soni, 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.
Generate agentic workflows using SAP-managed n8n in Joule StudioGenerate agentic workflows using SAP-managed n8n in Joule StudioSAP-managed n8n inside Joule Studio generates a workflow from a business intent a developer states, and the workflow is then tested and deployed, consuming line-of-business application APIs, events and agents in SAP Business AI Platform: process automation with the workflow generated from intent, and agent tooling where the workflow calls agents. The generated workflow sends notifications to the Joule Work mobile app of SAP Joule, to Microsoft Teams or to Slack. SAP's abstract names the pieces and not how the generation or the n8n hosting works. A two-hour hands-on TechEd 2026 session (Tuesday 27 October, Berlin), presented by Rama Sulakshani Murari, Rumen Dimitrov, Seshadri Sreenivas Ramanarayanan and Venugopal Chembrakalathil, 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.
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.
Knowledge graph and agent memory: Build an agent that remembersKnowledge graph and agent memory: Build an agent that remembersThe 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. DA205 on Tuesday 27 October is the 45-minute talk on the same engine, with a near-identical abstract and a different cast. A two-hour hands-on TechEd 2026 session (Wednesday 28 October, Berlin), presented by Christoph Morgen, Jan Zwickel, Markus Fath and Thomas Hammer, written here from SAP's abstract; the recording is not yet published.
Pro-Code AI AgentsPro-Code AI AgentsPro-code agents are the most flexible way the page frames building an agentic workflow on SAP BTP: full autonomy, custom API integrations and algorithms chosen by the developer, set against declarative alternatives such as content-based agents and Joule Scenarios. It names LangGraph as the framework it recommends for production, enterprise-grade agentic workflows, alongside the ReAct pattern as the plan-act-observe loop such an agent runs. That is the ground agent tooling covers, building an agent's own tool-calling loop rather than exposing an application to somebody else's agent.
SAP Joule for Consultants: Unified knowledge for requirements and designsSAP Joule for Consultants: Unified knowledge for requirements and designsFit-to-standard analysis as a consultant on a cloud transformation project: connecting an organisation's data to SAP Joule for Consultants through SAP AI Core, getting answers from SAP knowledge and that content, then building an expert, loading project files and running guided prompts. The edges are to SAP Joule, of which Joule for Consultants is a part, and to SAP AI Core, named as the connection path; how the data is grounded is left to the session. A TechEd 2026 hands-on session (Wednesday 28 October, Berlin), presented by Anantharaman Ravi, Natalie Han, Sachin Kaura and Yi Hsuan Lin, 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.
Transform business data into AI-supported insightsTransform business data into AI-supported insightsBusiness metrics turned into insights, narratives and recommendations by SAP Joule's agents, with People Intelligence, the SAP Snowflake solution extension for SAP Business Data Cloud and SAP Analytics Cloud connected in SAP Business Data Cloud. The abstract names what is connected and what comes out, and does not say what the exercise builds or where the Snowflake extension sits in it; People Intelligence and the extension are not atlas entries. A TechEd 2026 hands-on session (Wednesday 28 October, Berlin), presented by Babacar Toure, Maximilian Paul Gander, Neetha Pucknat and San Tran, 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.
Content filteringSAP only
Content FilteringContent FilteringContent filtering screens a large language model's input and output for low-quality, irrelevant or unsafe content: the four categories it names being hateful, violent, sexual and vulgar content, checking a request once on the way in and once on the way back. The page states smaller models can do this filtering efficiently, reading perplexity scores to flag anomalies, with the aim that SAP AI Core produces content meeting a stated safety standard, which is the ground content filtering covers on the BTP door.
Data maskingSAP only
Data MaskingData MaskingData masking replaces identifiable or confidential text in a prompt with placeholders such as <Person_0> or <Organization_1> before it reaches a large language model, using pattern matching and machine learning to find what to replace. The page states SAP AI Core supports it as a feature and sets out five steps for applying it, defining the masking scope, choosing a technique, preserving the prompt's intent, checking compliance and risk, then testing and monitoring the result. That is the shape data masking takes on the BTP door.
Document extractionSAP only
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.
Hands on SAP Document AI: Next-generation intelligent document processingHands on SAP Document AI: Next-generation intelligent document processingSAP Document AI configured and run by hand: schema design, splitting and classifying documents, enriching the extracted data and custom prompting are the exercises SAP's abstract names. Document extraction from the configuring side, with the schema the participant's own; which document types or models the exercises use is not stated. A TechEd 2026 hands-on session (Thursday 29 October, Berlin), presented by Christoph Lenschow, Tobias Weller and Tomasz Janasz, written here from SAP's abstract; no recording is announced.
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.
Use Free Tier to Create a Service Instance for SAP Document AIUse Free Tier to Create a Service Instance for SAP Document AIFour steps in the SAP BTP cockpit that end with a service key for SAP Document AI: open the cockpit, check the subaccount's entitlements and add the service on the free tier plan if it is not listed, create the instance, then create the key. It names the plans to use in production instead, blocks_of_100, embedded_edition and premium_edition, and stops at the credentials, before any document is uploaded.
Use Free Tier to Subscribe to SAP Document AI Basic UIUse Free Tier to Subscribe to SAP Document AI Basic UIEight steps from an entitled subaccount to the SAP Document AI basic UI open in a browser, and most of them are identity work rather than document work: getting a tenant for Cloud Identity Services, which the basic UI requires, activating the account and establishing trust with the subaccount, then subscribing, creating a user and assigning the Document_Information_Extraction_UI_Templates_Admin role collection. Using the UI to read a document is the subject of Use Machine Learning to Extract Information from Documents with the SAP Document AI Basic UI, which this tutorial names as what to read next.
Document groundingSAP and community
Building agentic applications with SAP HANA CloudBuilding agentic applications with SAP HANA CloudA CAP application extended with semantic search and agent features on top of SAP HANA Cloud's vector engine and SAP AI Core, built in a hands-on workshop. The abstract names the parts, CAP, the vector engine and AI Core, and the two additions: semantic search, the retrieval half of retrieval-augmented generation, and LLM-supported agent capabilities inside the application, which is agent tooling. Which embedding model, which CAP runtime and how the agent calls its tools are not stated. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Hui Li, Ritty Joseph, Shraddha Shetty and Tanuja Jadhav, 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.
Document GroundingDocument GroundingDocument Grounding is a managed retrieval-augmented-generation service under the Generative AI Hub on BTP, which SAP's page on SAP AI Core places inside that service: it ingests documents from Amazon S3, SharePoint, SAP Document Management Service, SAP Work Zone or an SFTP server, and handles chunking, embedding and retrieval itself, refreshing content automatically when a source document changes. The page states this managed path is recommended for most enterprise scenarios because it covers the whole lifecycle end to end, and offers a separate Document Grounding Vector API for data that is already chunked and embedded, for cases that need finer control over chunking and metadata.
LLM integrationSAP only
Access to Generative AI ModelsAccess to Generative AI ModelsSets out the plain way to call a deployed generative AI model on SAP BTP: a request that carries the prompt, the model and the parameters that control generation, with the same code able to switch between models. It lists data masking, prompt templating and filtering as features that come with the access rather than as code the caller writes, which is the shape LLM integration takes on the BTP door; the page's implementation sections sit behind its steps and were not read.
Agentic CAP: Build MCP servers and enterprise AI agentsAgentic CAP: Build MCP servers and enterprise AI agentsCAP applications become AI agents over the Model Context Protocol and the Agent2Agent protocol, which is the serve your application over MCP concern, and SAP AI Core is the LLM integration through which AI is embedded in a CAP app, with recommendations from the SAP-RPT-1 model as the abstract's example. The abstract names the two protocols and the one model and does not say which packages carry them. A two-hour TechEd 2026 session in a hands-on room (Tuesday 27 October, Berlin), presented by Daniel Hutzel, Daniel Schlachter, Marc Huber and Sami Lechner, 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.
Building agentic applications with SAP HANA CloudBuilding agentic applications with SAP HANA CloudA CAP application extended with semantic search and agent features on top of SAP HANA Cloud's vector engine and SAP AI Core, built in a hands-on workshop. The abstract names the parts, CAP, the vector engine and AI Core, and the two additions: semantic search, the retrieval half of retrieval-augmented generation, and LLM-supported agent capabilities inside the application, which is agent tooling. Which embedding model, which CAP runtime and how the agent calls its tools are not stated. A TechEd 2026 session (Thursday 29 October, Berlin), presented by Hui Li, Ritty Joseph, Shraddha Shetty and Tanuja Jadhav, written here from SAP's abstract; the recording is not yet published.
Content FilteringContent FilteringContent filtering screens a large language model's input and output for low-quality, irrelevant or unsafe content: the four categories it names being hateful, violent, sexual and vulgar content, checking a request once on the way in and once on the way back. The page states smaller models can do this filtering efficiently, reading perplexity scores to flag anomalies, with the aim that SAP AI Core produces content meeting a stated safety standard, which is the ground content filtering covers on the BTP door.
Data MaskingData MaskingData masking replaces identifiable or confidential text in a prompt with placeholders such as <Person_0> or <Organization_1> before it reaches a large language model, using pattern matching and machine learning to find what to replace. The page states SAP AI Core supports it as a feature and sets out five steps for applying it, defining the masking scope, choosing a technique, preserving the prompt's intent, checking compliance and risk, then testing and monitoring the result. That is the shape data masking takes on the BTP door.
Document GroundingDocument GroundingDocument Grounding is a managed retrieval-augmented-generation service under the Generative AI Hub on BTP, which SAP's page on SAP AI Core places inside that service: it ingests documents from Amazon S3, SharePoint, SAP Document Management Service, SAP Work Zone or an SFTP server, and handles chunking, embedding and retrieval itself, refreshing content automatically when a source document changes. The page states this managed path is recommended for most enterprise scenarios because it covers the whole lifecycle end to end, and offers a separate Document Grounding Vector API for data that is already chunked and embedded, for cases that need finer control over chunking and metadata.
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.
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.
Knowledge graph and agent memory: Build an agent that remembersKnowledge graph and agent memory: Build an agent that remembersThe 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. DA205 on Tuesday 27 October is the 45-minute talk on the same engine, with a near-identical abstract and a different cast. A two-hour hands-on TechEd 2026 session (Wednesday 28 October, Berlin), presented by Christoph Morgen, Jan Zwickel, Markus Fath and Thomas Hammer, written here from SAP's abstract; the recording is not yet published.
Prompt TemplatingPrompt TemplatingPrompt templating replaces a static prompt with a structured, reusable template whose placeholders are filled in at runtime, which the page says helps LLM responses stay consistent and lets the same instructions be adapted across tasks. On SAP AI Core this is implemented through the Prompt Registry, and the page states that storing prompts as plain strings in code is possible but not recommended. That is prompt management as a stored and managed object rather than a string embedded in the caller.
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.
SAP Joule for Consultants: Unified knowledge for requirements and designsSAP Joule for Consultants: Unified knowledge for requirements and designsFit-to-standard analysis as a consultant on a cloud transformation project: connecting an organisation's data to SAP Joule for Consultants through SAP AI Core, getting answers from SAP knowledge and that content, then building an expert, loading project files and running guided prompts. The edges are to SAP Joule, of which Joule for Consultants is a part, and to SAP AI Core, named as the connection path; how the data is grounded is left to the session. A TechEd 2026 hands-on session (Wednesday 28 October, Berlin), presented by Anantharaman Ravi, Natalie Han, Sachin Kaura and Yi Hsuan Lin, written here from SAP's abstract; the recording is not yet published.
SAP-RPT and TabPFN: Get started with tabular foundation modelsSAP-RPT and TabPFN: Get started with tabular foundation modelsTabular foundation models, SAP-RPT and TabPFN, in a hands-on with SAP and Prior Labs: the model families first, then predictions run through SAP AI Core with a workflow built on tabular orchestration and connected to the participant's own data for real-time predictions. A predictive models session with the models as the subject; the abstract does not name the SDK or API the workflow is built with. A TechEd 2026 hands-on session (Thursday 29 October, Berlin), presented by Eliott Kalfon, Janick Zaehringer-Frasch, Johannes Hoehne, Katharina Schell, Nilay Mehta and Sherene Tan, written here from SAP's abstract; no recording is announced.
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.
Predictive modelsSAP only
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.
Get hands on with tabular AI and forecasting models in SAP HANA CloudGet hands on with tabular AI and forecasting models in SAP HANA CloudPrediction and forecasting as predictive models inside SAP HANA Cloud, worked through hands-on: tabular AI models such as SAP-RPT-1 for on-the-fly predictions, time series foundation models for ad hoc forecasts, and the AutoML in the predictive analysis library. The abstract names the model kinds and the library and does not say how a model is called from SQL or from an application. A TechEd 2026 session (Wednesday 28 October, Berlin), presented by Christoph Morgen, Markus Fath, Ritty Joseph and Tanuja Jadhav, written here from SAP's abstract; the recording is not yet published.
SAP-RPT and TabPFN: Get started with tabular foundation modelsSAP-RPT and TabPFN: Get started with tabular foundation modelsTabular foundation models, SAP-RPT and TabPFN, in a hands-on with SAP and Prior Labs: the model families first, then predictions run through SAP AI Core with a workflow built on tabular orchestration and connected to the participant's own data for real-time predictions. A predictive models session with the models as the subject; the abstract does not name the SDK or API the workflow is built with. A TechEd 2026 hands-on session (Thursday 29 October, Berlin), presented by Eliott Kalfon, Janick Zaehringer-Frasch, Johannes Hoehne, Katharina Schell, Nilay Mehta and Sherene Tan, written here from SAP's abstract; no recording is announced.
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.
Prompt managementSAP only
Prompt TemplatingPrompt TemplatingPrompt templating replaces a static prompt with a structured, reusable template whose placeholders are filled in at runtime, which the page says helps LLM responses stay consistent and lets the same instructions be adapted across tasks. On SAP AI Core this is implemented through the Prompt Registry, and the page states that storing prompts as plain strings in code is possible but not recommended. That is prompt management as a stored and managed object rather than a string embedded in the caller.
Tool governanceSAP and community
Agentic AI Security & GovernanceAgentic AI Security & GovernanceNames seven threat categories agentic AI introduces beyond ordinary application security: prompt injection, excessive agency, supply-chain and model-integrity compromise, memory poisoning, improper output handling, resource abuse and agent-to-agent communication poisoning. Its answer is a defence-in-depth structure of security controls, input validation, privilege management, supply-chain checks, memory segmentation, output validation, execution quotas, secure communication, paired with governance and oversight: audit logging, explainability, human-in-the-loop review, fairness assessment and continuous monitoring. States the reason plainly: an agent decides, chains actions across turns, keeps memory between them and can act on real systems, a different risk profile from a single request-response call. That is the authorisation and audit-trail question tool governance is named for.
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.
Govern AI-supported actions across enterprise systemsGovern AI-supported actions across enterprise systemsGoverning what an AI agent may do once it takes business actions across enterprise systems, which is the Tool governance concern, with SAP Integration Suite as the place it is enforced. The abstract lists the mechanisms, scoped APIs, event-driven workflows, runtime policy enforcement, exception handling and observability across SAP and third-party systems, and names no Integration Suite feature behind any of them. A TechEd 2026 session (Tuesday 27 October, Berlin; also IN200V, virtual), presented by Finny Babu and Piyush Gakhar, written here from SAP's abstract; the recording is not yet published.
Intelligent, governed, and agentic integrations with SAP Integration SuiteIntelligent, governed, and agentic integrations with SAP Integration SuiteSAP Integration Suite positioned as the control plane that connects and governs agentic workflows across SAP and third-party systems, set against the abstract's claim that exposing back ends directly to AI brings security, compliance and cost risks. That governing role is the Tool governance concern; the abstract promises recent innovations and names none. A TechEd 2026 session (Wednesday 28 October, Berlin), presented by Finny Babu and Piyush Gakhar, 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.
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.
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