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As a subsidiary of thyssenkrupp, our technology helps reduce inventories and generate liquidity in the face of global uncertainties – from trade conflicts to pandemic risks to energy crises.
– Christian Jabs, CEO
Christian Jabs, you mentioned that two-thirds of all supply-chain decision-makers still rely on Excel. What exactly differentiates the use of your AI-powered models from the traditional work with spreadsheets?
pacemaker.ai’s AI models analyze extensive historical data spanning years, detect hidden patterns and anomalies, and integrate external influencing factors such as weather, holidays, exchange-rate fluctuations, or interest rates. Unlike Excel – where one usually draws simple trendlines or makes manual adjustments – we employ advanced machine-learning algorithms and ensemble models. We combine various methods like Random Forest, Gradient Boosting, and neural networks to deliver precise forecasts even in volatile markets. Ultimately, we achieve prediction accuracies that far surpass Excel-based calculations.
Which internal and external data sources do you need at a minimum to train your models – and what can a typical midsize company contribute from its existing IT infrastructure?
The basic prerequisite is your historical delivery data: what you shipped, when, in what quantity, and to whom. Every company has these data because they are indispensable for invoicing. In addition, we evaluate internal information such as inventory levels, production cycles, purchasing costs, and supplier performance. Qualitative data – like customer feedback or market research – can also be incorporated. Our experience shows that even midsize businesses with simple, well-structured datasets can train efficient models without having to build expensive infrastructure.
Trade conflicts and energy crises are real threats. What immediate advantages do decision-makers see, in this context, in AI-based forecasts compared to traditional planning approaches?
As a subsidiary of thyssenkrupp, our technology helps reduce inventories and generate liquidity in the face of global uncertainties – from trade conflicts to pandemic risks to energy crises. For companies within the supply chain, a ten-percent reduction in inventory can quickly save several million euros and lower interest costs by six-figure amounts per quarter. At the same time, early bottleneck detection can prevent production stoppages and make supply chains more resilient. These cost effects make AI forecasts attractive even to conservative decision-makers, as they combine long-term planning security with short-term flexibility.
You operate in the DACH region and in North America. Can you describe how your industry expertise and system integrations differ depending on the market segment?
We serve both SMEs and large enterprises – primarily in Germany, the DACH region, and across Europe, but also in the USA and Canada. Our software can be configured by industry – whether in the food and beverage sector, mechanical engineering, pharmaceuticals, or textiles – and integrates seamlessly with existing ERP systems like SAP, Microsoft Dynamics NAV, or Oracle. Through standardized APIs, we offer connections to CRM, e-commerce, and logistics platforms. A modular structure allows customers to subscribe only to the functions they need and to expand as required.
What does a typical project workflow at pacemaker.ai look like – from initial consultation and data-thinking workshops to the productive use of forecasts?
From kick-off to go-live, it usually takes four to six weeks. After a joint data-thinking phase – during which we define goals, forecasting horizons, and influencing factors – we train the first models and deliver the initial forecast. We then optimize parameters in agile two-week sprints, based on user feedback and live data. Our Customer Success team accompanies every step, trains users in workshops, and provides best-practice templates to ensure a smooth implementation.
Data security and sovereignty are central issues. Which certifications and technical measures do you employ to meet the highest compliance requirements?
Our platform runs in Microsoft Azure’s German data centers and meets the highest IT security standards, such as ISO 27001 and TISAX. As a subsidiary of thyssenkrupp, we already have strict guidelines that we implement thoroughly. Data access is encrypted exclusively via TLS, user rights are defined on a granular level, and audit logs document every change. Regular penetration tests, vulnerability analyses, and 24/7 security monitoring ensure that your sensitive information is protected at all times.
Your most recent feature addresses sustainability. How does your platform specifically help reduce CO₂ emissions, and which reporting tools do you offer for this purpose?
Our Sustainability Management Platform creates transparency in the supply chain and calculates CO₂ emissions from transportation, the corporate carbon footprint, and the product carbon footprint. Users receive detailed dashboards with emission metrics, comparative benchmarks, and scenario analyses. From the data obtained, concrete reduction measures can not only be derived and tracked continuously, but they can also be used seamlessly as an all-in-one solution for CSRD reporting or for creating a greenhouse gas inventory across Scopes 1–3.
What further developments and strategic partnerships do you plan to expand pacemaker.ai as a leading provider of “sustainably better”?
We continuously invest in new ML models, data sources, and APIs. Most recently, we acquired the Luxembourg-based company Waves to link AI forecasts with TÜV-certified CO₂ calculations and offer an integrated sustainability and forecasting platform. Our roadmap also includes the addition of real-time data streams, AI-driven scenario simulations, and an open platform for developers to integrate external modules. With these innovations, we stay at the forefront, create new use cases, and support our customers in becoming “sustainably better.” That is our motto.
A PUBLICATION BY SMART MEDIA