Practical AI accelerators, built to support senior delivery — not replace it.

SAP programmes generate a large volume of analytical and documentation work that is necessary but repetitive: reading legacy configuration, drafting specifications, tracing exceptions across logs and transactions. We use AI to reduce the effort and elapsed time these tasks take, while keeping the judgement, sign-off and accountability with our senior consultants and architects. The accelerators below are not chatbots layered on top of SAP, and they are not agents given standing permission to act — they are scoped tools applied to specific delivery problems, with a human decision point before anything produced is used.

Assessing a legacy Warehouse Management landscape ahead of an EWM migration means reviewing custom ABAP objects, interfaces, process variants and historical configuration decisions — usually under time pressure and across a landscape no single person has full visibility into. This accelerator reduces the effort required to assess legacy WM landscapes by structuring that analysis: it builds a consistent inventory of custom objects and interfaces, surfaces likely gaps against EWM standard capability, and drafts a first-pass view of migration scope and risk areas. Senior EWM architects then review, correct and validate that output before it feeds into scoping, backlog structuring or a business case — the assessment that reaches the client is the architects' assessment, produced faster.

Large SAP programmes run many workstreams in parallel, and functional specifications, technical designs, test cases and traceability matrices are where inconsistency between workstreams usually first shows up. This accelerator supports the generation, review and consistency checking of that documentation, which accelerates specification and test preparation without lowering the bar on what gets shipped to the programme. It is integrated using clean-core extension and approved SAP BTP API patterns — it does not bypass system governance or touch upgrade stability — and every draft is reviewed and adjusted by the functional or technical consultant accountable for that workstream before it is adopted.

Investigating a blocked Warehouse Task, an IDoc failure or a stock inconsistency in a live warehouse usually means navigating several SAP transactions, interface logs and automation-layer messages at once, under operational pressure. This accelerator reduces investigation time for warehouse exceptions by pulling the relevant log entries and system context together and proposing likely root causes for a qualified consultant to assess. It is read-only and advisory: it is connected via approved read APIs and SAP BTP extension patterns, it does not write to or modify any SAP system, and no corrective action is taken until a consultant has reviewed the recommendation.

The accelerators above are one side of how we use AI — tools that help ERP Factory consultants deliver SAP programmes faster. The other side is what AI could look like inside your SAP execution itself: agents that investigate operational exceptions in SAP EWM, TM, Order-to-Cash and Procure-to-Pay, correlate context, and recommend a governed action for a human to approve. We built an interactive AI Agent Lab to make that second idea concrete rather than theoretical — simulated SAP scenarios you can step through yourself, with the same human-approval principle running through every one.

These principles apply to every accelerator we build or deploy, without exception:

• Human review is required before any accelerator output is applied to a project or a live system
• No accelerator has standing permission to make autonomous changes to a production or non-production SAP environment
• Integration uses approved SAP and SAP BTP patterns only — clean-core extension, approved APIs, no governance bypass
• Data governance, security boundaries and deployment scope are defined per project, not assumed as a default