Scalable AI strategy shortens time-to-market – from hidden player to industrial frontrunner

The company had already built an internal data team – rich in expertise, but lacking real impact. After four years, only a single use case had made it into production. The reasons were clear: no strategic framework, no suitable platform, and no consistent understanding in management of why this mattered. Officially, the team reported to the CFO – in practice, it remained invisible. Data work took place, if at all, on the sidelines. 

What was missing was not commitment, but a clear roadmap, a powerful platform, and a use case that would demonstrate what was truly possible. 

Working closely with the company, the TIMETOACT GROUP began with a structured assessment: what was already in place, what was missing, and where the journey should lead. Skills, existing use cases, system landscape, and platform maturity were carefully analyzed. 

The outcome: an AI strategy that went beyond slideware, set clear priorities, and defined a robust roadmap – one that engaged both management and the operational team. Most importantly, it delivered a tangible target vision of what “good” should look like. 

To ensure the strategy didn’t remain theoretical, the next step was the build of a scalable AI platform – based on Microsoft Azure, seamlessly integrated into existing systems such as SAP BW/4HANA and PostgreSQL. The focus was on modularity and future readiness: CI/CD pipelines, API management, and an architecture designed not to block future use cases, but to accelerate them. 

In parallel, coaching-on-the-job took place: the goal was not just to build something, but to empower the company’s data team to independently develop new use cases going forward. 

Some use cases have the power to become true game changers. For this construction specialist, it was intelligent customer segmentation. The goal: to move away from scattergun campaigns and instead target audiences with precision, based on data. 

The challenge: The CRM system couldn’t handle the scale of over 1.1 million direct contacts – from architects to small craft businesses. 

The solution: AI logic was moved into the Azure backend, with results integrated directly into the CRM system via an intuitive interface. The system now analyzes historical purchase data, communication behavior, and CRM information, segmenting audiences automatically and with high accuracy. 

The impact? Instead of labor-intensive manual campaign creation, the company can now launch smart, data-driven targeting – five times faster than before. 

The success of customer segmentation didn’t just boost marketing efficiency – it also transformed the standing of the data team. Suddenly visible and recognized, the team became a strategic partner. Management is continuing to invest, with follow-up projects already underway: an AI model for cash flow forecasting to plan capital requirements more precisely, and another use case in R&D using computer vision to drive data-driven product innovation. 

This project was more than a platform build or the delivery of a single use case. It marked the beginning of a cultural shift: from reactive experimentation to a proactive, scalable data strategy. From isolated data processing to genuine business collaboration. 

Today, the company operates on a platform open to all use cases – whether structured or unstructured data. It has a data team that acts with confidence and recognition. And it views data not as an abstract resource, but as a lever for tangible competitive advantage.