Alcemy accelerates industry-wide AI adoption with new cement manufacturing transformation programme

Alcemy is repositioning itself from a point-solution provider to a broader enabler of artificial intelligence in cement manufacturing, as the Berlin-based industrial software company launches a new transformation programme for producers and sets out a longer-term ambition to automate grinding and concrete formulation.

The company, which has spent eight years building systems that predict cement and concrete quality in real time, says its software already works across 45 cement plants and more than 160 concrete plants in 18 countries. Its tools combine laboratory results with live production and process information, allowing operators to anticipate quality outcomes before conventional tests return and to adjust mill settings, clinker substitution and concrete recipes more quickly.

According to International Cement Review, alcemy’s latest move reflects a belief that the sector’s next bottleneck is no longer simply model accuracy, but the ability of producers to make data usable at scale. Chief executive Leopold Spenner said recent advances in generative AI had changed the question facing the industry, adding that the challenge was now how to make powerful software accessible to producers.

The new alcemy Foundation Partnership is designed to do just that. Rather than selling only standalone applications, the programme is intended to help cement groups harmonise fragmented plant data, build AI-ready architecture and develop their own internal expertise. It will bring together information from PLCs, SCADA systems, laboratory information management systems, SAP, MES platforms and plant sensors within a producer’s own cloud environment.

Alcemy says the aim is also to reduce long-term dependence on outside vendors by training internal teams to create dashboards, manage third-party AI systems and build proprietary applications. For now, the programme will be limited to one or two strategic partners from autumn 2026.

That shift towards enterprise-wide capability comes alongside a more ambitious automation roadmap. Alcemy says it is working towards fully autonomous cement grinding, building on its existing closed-loop optimisation platform. The next stage would incorporate more process data, online analysers and strength enhancers, while AI takes on increasing responsibility for mill control and the simultaneous optimisation of fineness and cement recipes.

Mr Spenner described the human role in that model as supervision rather than direct intervention, with staff focused on data quality and boundary setting instead of day-to-day set-point adjustments.

The company says more than a third of its cement customers already use the optimisation software in closed-loop mode. Earlier this year, alcemy also announced a partnership with ABB to link its quality-prediction system with ABB’s advanced process control and plant information management tools, a move aimed at supporting autonomous mill operation.

Alcemy is also extending its concrete platform, which monitors water additions, consistency and material variability to fine-tune recipes in real time. The company says this could cut cement content by between 5kg/m3 and 30kg/m3, depending on raw materials, performance requirements and the producer’s tolerance for risk. In practice, the achievable savings will vary with aggregate quality and how tightly a plant chooses to operate against specification limits.

The decarbonisation case is already visible in the market. ZKG reported that Spenner GmbH & Co. KG, Germany’s fifth-largest cement producer, has used alcemy’s software to help cut emissions by 65% through a lower-clinker product line. In that case, clinker content was reduced to below 30%, compared with about 80% in standard cement products, showing how AI-assisted quality control can support lower-carbon formulation without necessarily sacrificing performance or cost.

For alcemy, the broader argument is that artificial intelligence can support both sides of the sector’s decarbonisation challenge: lowering clinker factors and improving the operational stability needed for carbon capture systems. For industrial producers under pressure to cut emissions while maintaining throughput and product quality, that combination may prove more valuable than point automation alone.