SAP consolidated SAP BTP, SAP Business Data Cloud and AI Foundation into one platform for building and governing AI agents. We help you understand what this changes for your architecture, and we build on it.
SAP Business AI Platform brings together what previously lived in separate offerings: SAP Business Technology Platform, SAP Business Data Cloud and AI Foundation. For customers, this is less a new product to buy and more a consolidation of the stack many already run.
The heart of the platform is the context layer. The SAP Knowledge Graph encodes the semantic relationships of SAP business objects, so an AI agent does not just see tables, it understands what a purchase order is and how it relates to a delivery and an invoice. This is the difference between a language model guessing and an agent operating inside your processes.
We assess your readiness, select the right use case and deliver agents and applications in production.
We review your BTP landscape, integration architecture, data foundations and governance against what the platform expects, mapped to concrete use cases.
A discovery workshop qualifies and prioritizes use cases against available data, reachable processes and measurable outcomes. We say openly which ideas do not justify an agent.
Solution design on SAP Business AI Platform, with a fixed statement of work, clear deliverables and approval gates defined before development starts.
gents in Joule Studio, applications and workflows on SAP Build, registered in the AI Agent Hub and deployed into your environment with monitoring from day one.
User enablement, an adoption plan and post-go-live support, followed by an honest recommendation on whether and how to expand.
Agents that extract, validate and route documents through approval workflows, with human sign-off where amounts or exceptions require it.
Automated triage of blocked orders, missing data and delivery conflicts, resolving standard cases and escalating the rest with full context.
Continuous detection and correction proposals for duplicates, gaps and inconsistencies across SAP and non-SAP sources.
Assistants answering policy, status and process questions grounded in your actual data instead of a static FAQ.
Agents watching integration flows and business processes, flagging deviations before they become incidents.
AI steps inside workflows spanning SAP and non-SAP systems, built on the integration layer rather than around it.
A 30 minute conversation is usually enough to identify one worth building and two worth skipping.
Pick a slot that suits you. Thirty minutes, no obligation, with an architect rather than a salesperson. We will tell you honestly whether and how we can help.
It is a consolidation of SAP BTP, SAP Business Data Cloud and AI Foundation. If you run BTP, you are already on the foundation; specific AI services are licensed on top, and we help you understand which ones your use cases actually need.
No. Meaningful agent use cases can start on BTP with a solid integration layer. Business Data Cloud extends what agents can see, and whether you need it depends on the use case, not on the platform.
This is where integration architecture decides everything. Agents reach non-SAP systems through APIs and events, which is precisely the layer we build. In our own delivery practice, more than half of the integrations we implement on SAP Integration Suite connect non-SAP systems on both ends.
For qualifying customers, yes. SAP has launched a partner-led adoption program under which SAP funds delivery of AI projects by qualified partners.
Register them in the Agent Hub from day one, define approval gates for actions with business impact, and monitor consumption and behavior continuously. We design these controls into every delivery; our view on agent governance is covered in the newsletter.
SAP AI Core is a service for running and operating AI models and it continues to exist as part of the platform foundation. SAP Business AI Platform is the broader architecture around it: the Knowledge Graph, Joule Studio for agents, SAP Build for applications and the Agent Hub for governance.
Platform capabilities are licensed through your existing BTP commercial model, with AI services consumed through AI units. Consumption-based pricing rewards well-scoped use cases and punishes vague ones, which is one more reason to start bounded. We walk through the economics of your specific scenario before any commitment.
With foundations in place, a bounded use case typically goes from discovery workshop to production deployment in a few months.
Every major SAP announcement produces the same pattern: a wave of interest, a round of internal discussions, and then a quiet return to daily operations because nobody owned the next step. SAP Business AI Platform deserves better treatment, not because the marketing says so, but because the underlying shift is real. Agents grounded in business context, governed centrally and deployed on infrastructure you already operate are a different proposition from the chatbot experiments of the past two years. The organizations that will show results in 2027 are the ones that convert this announcement into one working use case in 2026, learn from its consumption data and expand from evidence rather than enthusiasm.
An AI agent is only as capable as the systems it can reach. APIs, event streams and integration flows determine whether an agent can read an order, verify an inventory position or trigger a workflow, which makes integration architecture the practical ceiling of every AI initiative on the platform. Data quality sets the second ceiling: an agent reasoning over incomplete or inconsistent master data produces confident answers to the wrong question. Governance sets the third, because agents that act inside business processes need defined approval gates and monitoring before deployment, not after the first incident. All three foundations are unglamorous, measurable and solvable, and they are where our work as integration architects begins.
