SAP AI Core

by SAP@sapWalldorf, GermanyNo ratings yet

Infrastructure for managing and running AI models, including generative AI hub access and custom predictive models.

Tool type: Enterprise AI model management and generative AI infrastructure service on SAP BTP
Made for: Enterprise teams and developers building production AI workloads on SAP BTP
Runs on: SAP BTP environment with SDK access from Python applications; Deployments run in SAP AI Core on SAP BTP; developers configure access and call models from local or hosted Python code using the SDK.
Last checked: 29 Oct 2026; 3 product sources

What it does

SAP AI Core takes in AI models and their deployments, including SAP-hosted, SAP-managed, and remote foundation models, grounding pipelines, and custom predictive models. It produces running model deployments and inference access for applications that call those models. Generative AI workloads are reached through the generative AI hub, and billing follows resource use.

Teams typically reach SAP AI Core through its Python SDK, which wraps model provider SDKs (OpenAI, Amazon, Google) and LangChain, or through the orchestration service. Configuration uses environment variables, a config file, or VCAP_SERVICES. Consumption can be reviewed in the SAP BTP cockpit by exporting the AI Core usage report.

SAP AI Core suits enterprise teams running production AI workloads on SAP BTP. Production use requires an enterprise account and a service plan: Standard for predictive workloads without generative AI, and Extended for generative AI hub access. Custom models incur compute, storage, and baseline costs, and foundation model usage is metered by tokens. Rates depend on the chosen model and resource consumption; consult the relevant SAP metering table before deployment.

What it can do

Deploy and manage custom predictive AI models with compute, storage, and baseline metering.
Access SAP-hosted, SAP-managed, and remote foundation models through the generative AI hub.
Use grounding pipelines with generative AI models.
Call LLMs and embedding models directly through per-model deployments.
Route requests through the orchestration service after creating an orchestration deployment.
Monitor generative AI hub model consumption and resource group consumption in the SAP BTP cockpit usage report.

Works with

SAP BTP cockpit usage export
OpenAI models via the Python SDK
Google models via the Python SDK
Amazon models via the Python SDK
LangChain

Example workflows

Calling a generative model through the SDK: Illustrative example. Input: a deployed LLM in the generative AI hub and a prompt. Steps: install the Python SDK, set AICORE_* configuration variables, create or select a model deployment, and call the model class. Output: a model response, with token usage recorded for billing.
Reviewing AI Core consumption: Illustrative example. Input: a global account in SAP BTP. Steps: open the cockpit, select Usage, filter by AI Core, and click Export. Output: a report listing generative AI hub model consumption under Applications and resource group consumption under instance.

Before you choose

Generative AI hub access requires the Extended plan; the Standard plan does not include it.
Custom predictive workloads can incur baseline, compute and storage charges. Generative workloads have model-specific meters and capacity-unit conversions.
The default SDK install includes only OpenAI models; Google and Amazon models require the extras in square brackets.

Listed under

Data

Get started

Create deployments for each model or an orchestration deployment before calling models; the 30-day basic trial offers a guided generative AI hub environment.

Create an enterprise account and select the Standard or Extended service plan for AI Core, based on whether generative AI hub access is needed.
Create a deployment for each model you want to call directly, or an orchestration service deployment for orchestration access.
Install the SDK with pip (for example, pip install "sap-ai-sdk-gen[all]") and set AICORE_CLIENT_ID, AICORE_CLIENT_SECRET, AICORE_AUTH_URL, AICORE_BASE_URL, and AICORE_RESOURCE_GROUP, or use a config file at ~/.aicore/config.json.

Set up SAP AI Core

Plans and prices

Custom models can incur baseline, compute and storage costs. Generative AI hub requires Extended and uses model-specific metering. A guided 30-day basic trial is separate from a production service entitlement; consult SAP’s current rate table.

We couldn’t find published prices for SAP AI Core. See their pricing page ↗

30-day free trial.

Sources for this overview

Product pages, documentation, and pricing checked 29 Oct 2026. Each source supports part of the overview; availability and prices can change.

Metering and Pricing for SAP AI Core | SAP Help Portal ↗help.sap.com
SAP Cloud SDK for AI (Python) - generative | SAP Cloud SDK for AI ↗sap.github.io
Service Plans | SAP Help Portal ↗help.sap.com

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Last checked 29 Oct 2026. Every field keeps its source and date; unknown means we couldn’t confirm it.