Most AI projects in steel and metals trading do not fail on the models themselves, but on the master data and processes in the underlying ERP system. Often this only becomes visible once the budget has already been approved. This is exactly where Zirkel Technologies GmbH comes in with its Data & AI Readiness Assessment: it tests whether the existing SAP or Microsoft Dynamics 365 environment can support operational AI at all - before money goes into models, platforms or use cases. The assessment shows how well an SAP or Dynamics 365 environment supports operational AI. It evaluates the quality of master data in material and customer records, interface and integration capability, data availability for the operationally relevant use cases - stock, processing, on-time delivery, pricing - and the connection to downstream data platforms, including MuleSoft-based pipelines and Databricks architectures.
That the data foundation - not the model - decides between success and failure is borne out by current figures from Germany's industry association Bitkom: in a survey of 555 industrial companies, 57 percent name missing data and 48 percent inadequate IT infrastructure as reasons why such projects frequently fail (Bitkom, 2025). At the same time, only six percent of companies consider the full potential of their own data realized (Bitkom, 2024). This is precisely the gap the assessment addresses - before the investment in models and platforms is made.
"AI projects in steel trade rarely fail on the technology and almost always on the data foundation. If master data, interfaces and processes in the ERP won't carry the load, even the best model won't help. That is exactly the gap we close — before it becomes an investment risk." Kapil Gupta · Managing Director, Zirkel Technologies GmbH
About Zirkel Technologies
Zirkel Technologies GmbH, operating from Frankfurt am Main with locations in Vienna, Zurich, Oakville, Riga and Noida, has been active since 2016 as a vendor-neutral consulting and implementation firm for enterprise technology (SAP, Salesforce, Microsoft Dynamics 365, MuleSoft) in the industrial Mittelstand - with sector focus areas in machinery and plant engineering, metal processing, steel and metals trading, and the paper and chemical industries. The company's data and AI team comprises Databricks-certified engineers across the Machine Learning, Data Engineering and Data Analyst tracks, complemented by a partnership with Dataciders for Microsoft Fabric-based data and AI platforms.
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