AI Adoption
We prepare your SAP data and processes for AI and stand up the underlying platforms, including OpenAI and Anthropic's FedRAMP / GovCloud offerings, and fully air-gapped on-prem LLMs for organizations that cannot send data to the public cloud.
What we deliver
- AI use-case prioritization for SAP estates
- OpenAI and Anthropic FedRAMP / GovCloud deployments
- Closed-loop and air-gapped LLM stand-up
- Data structuring and grounding for AI/ML
- Joule, SAP Build, and custom agent integration
Talk to a ai adoption expert
Our consultants average 15+ years in SAP for A&D and GovCon. No offshore handoffs.
Schedule a call →Our approach
AI adoption in regulated environments fails when the approach is driven by technology enthusiasm rather than use case prioritization. Our approach starts with identifying the specific SAP processes where AI delivers measurable value: invoice matching, anomaly detection in cost accounting, predictive maintenance scheduling, intelligent project forecasting, natural language querying of program data. We prioritize use cases by value, feasibility, and the security posture required to execute them.
The second step is infrastructure. For clients operating in FedRAMP or GovCloud-authorized environments, we deploy on OpenAI and Anthropic's compliant offerings. For clients handling classified data or operating under constraints that prevent any data from leaving their network boundary, we stand up fully air-gapped LLM deployments on dedicated hardware inside their secure enclave. The infrastructure choice is driven by the data classification of your workloads, not by cost.
The third step is data preparation. AI models are only as useful as the data they can access. We structure your SAP master data, transactional data, and documents so that AI systems can reliably retrieve and interpret them. We ground AI outputs in verified source data so that answers cite SAP records rather than generating plausible but unverified responses.
Outcomes you can measure
A RevTech AI adoption engagement produces a prioritized use case portfolio, an infrastructure environment matched to the security posture of your workloads, a data grounding approach that connects AI outputs to source-of-truth SAP data, and a production deployment of at least one AI use case with measurable business impact.
Measurable impact typically includes reduction in manual processing time, improvement in anomaly detection coverage, and faster access to program-level insights that previously required analyst time to compile. The AI is accountable to business outcomes, not to model sophistication.
Where this fits in your SAP roadmap
AI Adoption applies when your SAP environment is stable enough to support additional workloads, and when your organization has identified specific operational inefficiencies that AI could address. It is not a first move for an environment still stabilizing after a major implementation.
For organizations with unclear AI strategy, a use case prioritization engagement is often the right scoped starting point. For organizations with a clear direction but infrastructure constraints, our air-gapped and GovCloud deployment capabilities are typically the critical path.
Common questions
Ready to transform your SAP landscape?
Let's discuss how RevTech can accelerate your mission, whether you're scoping a Greenfield S/4HANA build, modernizing a legacy estate, or planning your AI roadmap.