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SAP AI Services - DOX - Gen AI with SAP CAP Plugin - Part 3
Building on Reusable components for CAP with cds-pluginReusable components for CAP with cds-pluginThe post that taught the mechanism, and it teaches it by picking a requirement small enough to be absurd: every string a service returns should end in a random emoji. Working through that on the bookshop example leaves nothing to argue about except the plumbing, which is the point — what a cds-plugin is, where it hooks in, and why packaging it beats copying it into the next project. Vinícius Barrionuevo credits this post as the thing that gave him the idea for sap-cap-sdm-plugin, and it is hard to read the plugin ecosystem in this graph without it.published 2023-04-30 by Daniel SchlachterDaniel Schlachtercreated 9 pieces, contributed to 10 entriessap official, this part walks through a custom CAP plugin — a cds-plugin.js plus a lib_cap_dox.js helper — that authenticates against SAP's Document Information Extraction (DOX) service and calls its schema and job-status APIs to fill an entity from extracted document fields. It covers reading the service key from Cloud Foundry (cf service-key) for the OAuth token endpoint, and dynamically mapping DOX's header and line-item output onto CAP entity properties.
Where it sits
Explains
Plugin authoringCAPPlugin authoringWriting a package that extends a framework or runtime rather than an application that uses it — a reusable extension loaded by its host, and the question you arrive at once solving a problem twice makes you want to solve it once for everyone.Document extractionCAPBTPDocument extractionGetting structured data out of a document somebody sent you — an invoice, a purchase order, a scanned form — instead of having a person key it in. The mirror image of document output, and a different problem from reading a service: the input is a file, the shape is unknown until something reads it, and the answer arrives with a confidence rather than a guarantee.
Source
reachable
Who is behind it
sabarna17author
In this series
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Properties
About this work
For document-extraction
Applies in
Group by16 of 16 pieces
Piece, what it offersStill applies
What's in Daniel Hutzel's brain?What's in Daniel Hutzel's brain?A Devtoberfest 2026 session in the building-apps track, in which Daniel Hutzel and DJ Adams work through what the CAP team is building for agents. A bookshop gets an MCP endpoint beside its OData one from a single annotation, with the plugin writing the coding agent's configuration itself; in the xt-travels sample five services that know nothing about each other are served over MCP and an agent does the orchestration the hand-built UI and its value helps used to do. Hutzel then annotates a service as an agent so the ReAct loop and the choice of model move into the CAP service, and finally drops MCP for a skill that teaches the agent CQL instead, which is where the edges to Serve your application over MCP, Agent tooling and Agent guidance come from. The mechanism under all of it, a plugin file in the package root and event handlers that can be added to any CAP service, is the edge to Plugin authoring.published 2026-10-02
DRY CAP – Making Sustainable Solutions Through PluginsDRY CAP – Making Sustainable Solutions Through PluginsA Devtoberfest 2026 building-apps session on packaging the things you would otherwise write twice, from in-house API clients and shared data models to validation logic, as a CAP plugin. The presenter builds one live: a cds-plugin.js next to package.json is what makes CAP notice the plugin at all, an index.cds carries a reusable user context and service that the consuming application projects into its own and protects there, and the plugin registers an Express middleware at a chosen step of the bootstrap to put user properties on the request. A feature-flagging plugin his team already uses closes it, and the whole walkthrough is the edge to Plugin authoring.SAP Developers, published 2026-10-02
Why Our First Document AI Exercise Was a Résumé, Not an InvoiceWhy Our First Document AI Exercise Was a Résumé, Not an InvoiceWorking through a SAP Document AI workshop, the author explains why its exercises teach extraction on a résumé before an invoice: a résumé has no stable layout to map fields against, so it forces the point that the tool extracts from a written description of a schema rather than from position-matched templates. Describing the schema is shown to carry real judgment — what a missing end date should become, what a vague field name like "number" costs the model, who in a company should decide these things — and the piece argues that preparing for a project is chiefly a business task of writing down knowledge that otherwise stays in people's heads.Mariano_BacaStorni, published 2026-09-03
What a Second Document AI Workshop Taught Me About GovernanceWhat a Second Document AI Workshop Taught Me About GovernanceFrom questions raised at a second SAP Document AI workshop: the retention period for extracted data is a setting in the service's administration rather than a fixed property, with the source file deleted after processing and the decommissioning period for the extracted data configured to the customer's own policy. It also draws a boundary readers kept merging: Document AI extracts across languages but does not translate, so turning a document into a reviewer's own language is a separate step, pointing on BTP at SAP Translation Hub.Nicolas_BacaStorni, published 2026-08-25
Connecting SAP Integration Suite with SAP Document AI and SAP Business AIConnecting SAP Integration Suite with SAP Document AI and SAP Business AIWalks through a Cloud Integration flow in SAP Integration Suite that pulls PDF purchase orders from a Gmail mailbox, extracts header and line-item fields through SAP Document AI's job-submission and polling API, and validates the result with SAP AI Core's generative AI hub using GPT-5-mini as a quality check rather than the source of the extracted values. Groovy steps combine the Document AI confidence score and the model's score into one figure that routes low-scoring purchase orders to manual review, with no S/4HANA posting performed.subhojitSaha, published 2026-08-24
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
Integrate CAP application as outbound channel for SAP Document AIIntegrate CAP application as outbound channel for SAP Document AIDocument AI will call you back when extraction finishes, and the callback is where this goes wrong: the CAP application has to accept an unauthenticated POST from outside without dropping CSRF protection for everything else. The answer is a middleware hooked into the CAP bootstrap, and the post spends its length on the token lifecycle rather than on the extraction.sdeissenboeck, published 2026-04-22
Integrating SAP Document Information Extraction (Document AI) with SAP CAP – Step by StepIntegrating SAP Document Information Extraction (Document AI) with SAP CAP – Step by StepThe forward direction, in full: a PDF or scan arriving at a CAP service, sent to Document Information Extraction, and the fields coming back into the model. Long, and step-by-step in the literal sense — the service binding and the request shapes are all written out.furkan5, published 2025-10-09
Cloud Integration with Document AICloud Integration with Document AIWalks through connecting Cloud Integration to SAP Document AI: an iFlow posts a prescription PDF to Document AI's job API, polls the job endpoint until it completes, and a groovy script reads back the result, keeping only the fields above a stated 60% confidence threshold. The scenario is a hospital extracting a new patient's past illnesses, allergies and blood group from uploaded prescriptions, matched against a custom extraction schema.PriyankaChak, published 2025-08-10
Create your first CAP pluginCreate your first CAP pluginA step-by-step guide to the cds-plugin.js extension point: scaffold a package, add an index.cds for shared model artifacts, and test it locally against a throwaway CAP project before publishing to npm, with a separate section on building the same plugin in TypeScript and compiling it with tsc. Points to the author's own cds-plugin-handlers and ui5-cap-serverside-rendering-plugin as worked examples.published 2024-12-09
How to build reusable plugin components for CAP Java applicationsHow to build reusable plugin components for CAP Java applicationsA companion to Daniel Schlachter's Reusable components for CAP with cds-plugin, showing the same mechanism on CAP Java: a plugin ships as its own Maven artifact with an event handler and a CdsRuntimeConfiguration implementation, registered through the JDK's ServiceLoader rather than any CAP-specific wiring. The walkthrough builds a cds-emoji-plugin-java jar that decorates @emoji-annotated fields on read, installs it to the local Maven repository, and adds it as a runtime dependency to a cds init --add java bookshop application. It argues the plugin mechanism was not new to CAP Java, just previously undocumented.robinjayasinghe, published 2023-05-16
BTP CAP : Custom plugin to separate generic change log capture logicBTP CAP : Custom plugin to separate generic change log capture logicWalks through building a custom [CAP](ecosystem:cap) plugin that centralises change-log capture: on cds.once('served') it collects entities annotated @audit, then hooks srv.before('UPDATE') to read the existing record, diff it field by field against the incoming payload, and record old/new values with the user and timestamp. It also documents a cds build failure packaging the plugin's own directory into gen/srv for MTA deployment, fixed by adding it as a copyfiles build-parameter step in mta.yaml.sreehari_vpillai, published 2023-05-10
Reusable components for CAP with cds-pluginReusable components for CAP with cds-pluginThe post that taught the mechanism, and it teaches it by picking a requirement small enough to be absurd: every string a service returns should end in a random emoji. Working through that on the bookshop example leaves nothing to argue about except the plumbing, which is the point — what a cds-plugin is, where it hooks in, and why packaging it beats copying it into the next project. Vinícius Barrionuevo credits this post as the thing that gave him the idea for sap-cap-sdm-plugin, and it is hard to read the plugin ecosystem in this graph without it.published 2023-04-30
AI needs a foundation: A map of the plug-in ecosystem for CAPAI needs a foundation: A map of the plug-in ecosystem for CAPA map of the plug-ins for CAP (@sap/cds), official, community and independent, drawn across regions such as integration, performance and tooling, so that a team can see what exists to reuse and what it would have to build: the question plugin authoring answers from the other side. SAP's abstract places CAP at the centre of its AI strategy, with model context protocol support, and the map is offered as the foundation under that. A TechEd 2026 session (Tuesday 27 October, Community Theater, Berlin), presented by Mike Zaschka, 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.
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.
Details
Graph
Plugin authoringcapability, core only
Document extractioncapability, core only
SAP Communitypublishing source
SAP Communitycloud-foundry-tag
Source
Type
blog
Published on
Host
community.sap.com
Discovered via
First seen
History
- explains → applies_to on capability:document-extraction (cap, btp)Door scope proposed from the title and summary, so a door page lists the piece only where it holds (docs/concepts/content-on-doors.md).
- Entered the atlasDiscovered via SAP Community · cloud-foundry-tag.
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